Urban Science doi: 10.3390/urbansci10060336

Authors: Gilberto Duarte Carlos Sérgio Padrão Fernandes

João António de Aguiar was one of the most prolific Portuguese architect-planners of the twentieth century, producing an extensive body of work within the framework of the 1934 legislative reform. He employed Urban Development Plans as a key scientific and technical instrument for territorial intervention, both in mainland Portugal and in the overseas territories. Despite his significance, Aguiar’s contribution remains relatively understudied, frequently overshadowed by the reformist ministry of Duarte Pacheco and by the dominant ideological narratives of the period. This article advances a critical analysis centred on urban composition and city design, with particular emphasis on the transformation of coastal urban structures and on Aguiar’s interventions in the Portuguese colonial context. Through a comparative and interpretative methodology, the study examines the formal and spatial principles underpinning his plans, while addressing the cultural challenges involved in adapting European urban models to non-European contexts. By shifting the focus from a merely descriptive inventory of planning instruments to a deeper investigation of urban form, this research offers a more nuanced reading of urban transformation processes in overseas coastal settlements. It contributes to a clearer and more structured understanding of Aguiar’s influence on African and Asian urbanism and on colonial planning practices more broadly.

Urban Science doi: 10.3390/urbansci10060335

Authors: Reem Al Sharif Shaligram Pokharel

Smart cities encounter numerous risks, including technical and non-technical risks, on account of exchanging large volumes of data for different services; therefore, understanding and assessing risks for their management becomes essential. In this paper, a risk assessment framework for smart cities, based on a BLOC-ICE systems approach, is proposed. The framework outcomes are analyzed based on the data collected from a sample smart city to understand the importance of risks and the ways to mitigate or avoid such risks. The analysis of risk in the framework is based on the Dempster–Shafer and Bayesian theories, which can be used to assess the risk and its impact based on a particular smart city environment. In this paper, the focus is on design phase risks. The outcome of the analysis shows that strategic risks, stakeholder engagement, regulatory compliance, business continuity, and financial risks are important during the design phase and decision makers should develop measures to address these risks, which, otherwise, can have consequential impacts during the development and operation phase. The paper also provides some research direction on risk assessment.

Urban Science doi: 10.3390/urbansci10060334

Authors: Atakilti Brhanu Kiros Jonathan Dortheimer Noam Teshuva Achituv Cohen

Urban planners need scalable ways to monitor pedestrian conditions across heterogeneous cities, but conventional Level-of-Service (LOS) methods are often locally calibrated and difficult to transfer. This study proposes a city-adaptive framework for pedestrian LOS mapping using spatio-temporal graph models and few-shot transfer learning. Pedestrian count data from Melbourne, Dublin, and Zurich were converted into six ordinal LOS classes using city-specific percentile thresholds computed from the training data, yielding a relative congestion measure rather than an absolute cross-city standard. We developed a spatio-temporal graph transformer with an ordinal prediction head and evaluated it under in-domain, zero-shot, few-shot, and domain-adaptive settings. The results show strong in-domain performance in Melbourne (accuracy 79.7%; Acc ± 1 99.1%) and effective adaptation to the city-adaptive ordinal classification task. Few-shot fine-tuning with only 5% labeled target city data recovered 95–99% of in-domain performance, suggesting that small amounts of local supervision can substantially reduce calibration requirements in data-scarce environments. KernelSHAP analysis indicates that short-term temporal lag features dominate predictions across cities, whereas spatial and contextual features vary more strongly with local urban structure. The findings suggest that few-shot transfer learning can support pedestrian LOS estimation in cities with limited labeled data; however, the proposed LOS formulation should be interpreted as a city-specific relative indicator rather than an absolute measure of pedestrian comfort, crowding, or service quality. While the framework was evaluated across three cities, additional validation in diverse urban contexts and against perceptual measures of pedestrian experience remains necessary. Overall, the study contributes a city-adaptive framework for transferable relative LOS prediction rather than a universal cross-city LOS standard.

Urban Science doi: 10.3390/urbansci10060333

Authors: Yan Zhang Weijun Gao Nan Zhang Wei Tan

Quasi-Industrial Districts (QIDs) in Japan allow the coexistence of industrial, residential, and commercial functions. However, under pressures such as deindustrialization, demographic decline, and urban restructuring, their functional balance has been increasingly disrupted. This study investigates the spatiotemporal evolution of QIDs in Kitakyushu and develops a GIS-based framework to quantify changes in land-use structure. Using historical zoning and building floor-area data from 1986 to 2024, ternary diagram analysis is applied to examine relationships among the three functional types and identify transformation trajectories. Results show that while the total QID area expanded by 38.8%, internal structures changed significantly. Industry-dominant districts declined, commerce-oriented districts increased, and residential–industrial mixed types largely disappeared, indicating a shift toward commercial and residential functions. These findings reveal a growing mismatch between zoning designations and actual land use. To address this, the study proposes combining industrial concentration with clearer residential zoning, supported by periodic evaluation based on functional deviation thresholds. The framework provides a quantitative tool for adaptive land-use governance in shrinking industrial cities.

Urban Science doi: 10.3390/urbansci10060332

Authors: Ioannis Chatziioannou Panagiotis Kanellopoulos Charalampos Kyriakidis Argyris Stagias Efthimios Bakogiannis

The authors would like to make the following correction to the published paper entitled “Bridging Perceptions: A Comparative Evaluation of Public Space Design Qualities by Experts and Users” [...]

Urban Science doi: 10.3390/urbansci10060331

Authors: Nikhita Kannam Mahdieh Allahviranloo Laure Alice Raymonde Vatin

Multi-day travel diaries are often associated with high rates of partial completion, limiting their value for activity-based demand modeling. This paper develops a probabilistic framework that encodes daily activity sequences, clusters them with a Gaussian Mixture Model (GMM) to obtain soft (probabilistic) memberships, and predicts missing days through a constrained Lagrangian regression that guarantees valid probability distributions. Applied to the New York City Citywide Mobility Survey for 2019 and 2022, the soft-clustering approach achieves an RMSE as low as 0.17—substantially outperforming hard-clustering baselines (16–36% accuracy)—and reconstructs population-level time-use profiles with approximately 5–6% mean absolute error. Results show that post-pandemic activity patterns are more home-anchored and less varied, with pronounced socioeconomic divergence in recovery trajectories.

Urban Science doi: 10.3390/urbansci10060330

Authors: Olena Zayats Oksana Mulesa Mykola Palinchak

Disruptions in urban supply chains increase the risk of reduced access to medicines whose continuous availability is important for public health. This article develops an open-data decision support system (DSS) framework for assessing medicine availability under shortage and node-failure scenarios. The empirical application combines redeemed e-prescription data from the Ukrainian reimbursement program for 2022–2025 with the registry of dispensing points under National Health Service of Ukraine contracts and applies a unified scenario design to Kyiv and Lviv. The results show that demand is more concentrated in Lviv: the top 10 dispensing nodes account for 29.7% of redeemed e-prescriptions, compared with 14.2% in Kyiv. The proposed DSS supports the redistribution of limited available volume across spatial zones; it does not generate additional supply. Its value lies in identifying where lower-tail coverage, service coverage gaps, and redistribution-distance constraints should be monitored under explicitly defined stress-test assumptions. The framework is therefore positioned as a scenario-based planning tool rather than as a real-time inventory-management system.

Urban Science doi: 10.3390/urbansci10060329

Authors: Marta Luz Arango Uribe Julian Sanchez Corredor Cristian David Correa Álvarez

Background: Urban road-traffic fatalities are a public health burden and a governance challenge because protection is uneven across urban space and time. Methods: We analyzed 702,540 administrative road-incident records from Medellín, Colombia (2008–2025), identified 2762 fatal cases, standardized incident categories, and harmonized time and coordinate fields. Spatial analyses were based on 2507 geocoded fatalities. We combined descriptive profiling, chi-square tests, logistic regression comparing pedestrian-strike and collision fatalities, sensitivity analyses using grouped time periods and a pandemic-period indicator, and spatial autocorrelation measures using Moran’s I and Getis–Ord Gi*. Results: Incident type composition did not differ significantly between daytime and nighttime, but it varied across districts (comunas). Each later hour was associated with slightly higher odds that a fatality would be classified as a pedestrian strike rather than a collision (OR = 1.033), and fatalities in the urban core had nearly threefold higher odds of being classified as pedestrian strikes (OR = 2.953). Sensitivity analyses did not materially alter these associations. Spatial statistics showed strong clustering among the dominant fatality classes and identified 129 significant hotspot cells. Conclusions: Fatal road-traffic harm in Medellín is spatially concentrated and varies by incident mechanism, with pedestrian fatalities disproportionately concentrated in central areas of intense pedestrian–vehicle interaction. These findings show that transparent surveillance analytics can inform governance prioritization while also underscoring the need to improve data completeness, incorporate exposure measures, and interpret pandemic-period patterns with caution.

Urban Science doi: 10.3390/urbansci10060328

Authors: Renata Činčikaitė

Road transport is one of the most significant sources of environmental pollution and greenhouse gas emissions; therefore, the development of sustainable mobility is becoming an important direction of urban transport policy. The objectives of the European Union’s transport policy encourage cities to plan and implement measures that reduce the environmental impact of transport, improve transport conditions, and increase the availability of mobility alternatives. The aim of this study is to evaluate the planning of sustainable mobility development in Lithuanian cities by analysing sustainable urban mobility plans, the measures proposed in them, and their links to the needs of urban transport systems. The study applied descriptive statistics, comparative analysis, and document content analysis methods. The urban plans of Lithuanian cities were evaluated according to the following criteria: the time scope and relevance of the plan, the completeness of the analysis of the existing transport system, the assessment of the environment and quality of life in cities, and the compliance of the planned sustainable mobility measures with the needs of the city. The results of the study show that only a portion of Lithuanian cities have prepared sustainable urban mobility plans, and their contents and analytical bases differ. Some of the plans do not provide a sufficiently detailed and relevant analysis of the current situation; therefore, the need for the selected measures is not always clearly justified. The cities analysed generally envisage or apply measures to improve public transport, develop pedestrian and bicycle infrastructure, regulate traffic, create electric vehicle infrastructure, and promote multimodality. It was concluded that sustainable mobility planning in Lithuanian cities is uneven, and its assessment depends not only on the diversity of the envisaged measures but also on the analytical quality of planning documents, the justification of measures, and the consistency of envisaged implementation measures. The study highlights the need to strengthen data-based sustainable mobility planning and to more clearly link the measures envisaged in the plans with the specific challenges of urban transport systems.

Urban Science doi: 10.3390/urbansci10060327

Authors: Gayanthi Krishani Perera John Abeysiri Munasinghe Madhushika Gihanthi Munasinghe Rathnayake Kankanamge Nethmi Prabudya Piyasena Rangika Umesh Halwatura

Rapid urbanization in tropical Asia has led to a critical loss of green cover, exacerbating urban environmental challenges. While green roofs offer a promising Nature-based solution, their implementation in Asian countries is hindered by the prevalence of sloped roofs and high structural conversion costs. This research addresses this gap by developing a novel, lightweight vegetative roof tile designed as a direct structural replacement for conventional roofing materials in Sri Lanka. Existing roofing systems were studied, followed by a laboriousness study to determine the optimum tile dimensions. To meet these requirements, a modular tile measuring 900 mm × 1200 mm with a wave-shaped corrugated profile (a 10 mm rise and a 200 mm pitch) was engineered using SolidWorks 2024 and ABAQUS 2024 to meet Eurocode standards. Field investigations into plant health helped to finalize the depth of the roof tile as 2.5 cm. Following root penetration testing, fiber-reinforced plastic was selected for the tile structure to ensure durability while maintaining a total saturated weight of 52.5 kg/m2. Biological testing demonstrated robust greening performance, with Axonopus compressus and Zoysia matrella achieving 100% survival rates and over 80% canopy coverage. This design methodology can be adapted across tropical Asia, contributing significantly to regional green infrastructure development and sustainable building practices.

Urban Science doi: 10.3390/urbansci10060326

Authors: Antonio Verde Miguel Meléndez-Useros Fernando Viadero-Monasterio

Urban mobility is undergoing a rapid transition driven by digitalization, electrification, and automation. However, current research remains largely fragmented across specific technological domains, obscuring the interactions required for city-scale deployment. To address this gap, we conducted a literature review (2018–2026) adhering to the PRISMA 2020 guidelines. Using Google Scholar as an aggregate search engine, we screened and synthesized 162 peer-reviewed studies across four foundational pillars: intelligent transportation systems, resilient infrastructure, electric mobility, and autonomous/connected vehicles. The methodological evaluation of the literature reveals a prevalent overreliance on simulation models compared to large-scale field trials. Through a narrative synthesis of the selected studies, we derive a comprehensive five-layer conceptual framework that integrates the infrastructure, mobility, energy, digital, and governance layers. The findings indicate that scaling smart mobility is frequently constrained by institutional fragmentation and infrastructure rigidity, which often act as bottlenecks equal to or greater than technological capability. The review concludes by outlining targeted research priorities to guide the integration of sustainable urban mobility.

Urban Science doi: 10.3390/urbansci10060325

Authors: Feng Tang Lei Chen Lingxuan Zeng Yaqin Nie Jian Yang

Adverse weather and low-illumination conditions in urban road scenarios substantially degrade license plate image quality, posing a major challenge to robust automatic license plate recognition for urban intelligent transportation systems and smart city construction. To address the limitations of conventional pipelines that optimize detection, enhancement, and recognition in isolation, this study proposes CLEI, a unified framework integrating YOLOv12-based detection, GAN-based image enhancement, and a novel CNN–Mamba network (CMN) for character recognition. Using a curated dataset of 3000 license plate images captured under rain, snow, fog, and nighttime urban roadside conditions, we first benchmarked several mainstream detectors and identified YOLOv12s as the most effective model in terms of accuracy, inference speed, and computational efficiency. To mitigate blur and low-quality degradation in cropped plate regions, DeblurGAN-v2 was employed for adaptive enhancement, achieving PSNR of 16.61 dB, SSIM of 0.8776, and LPIPS of 0.1151. For recognition, the proposed CMN replaces the recurrent module in CRNN with a Mamba-based state-space model, improving sequence modeling efficiency and robustness. CMN achieved 93.3% plate accuracy, outperforming CRNN (91.0%) and LPRNet (88.5%), while the full CLEI framework reached 93.67% accuracy after enhancement. These results demonstrate that collaborative optimization across detection, restoration, and recognition enables accurate and efficient license plate recognition in severely degraded urban traffic environments, providing a reliable technical support for urban traffic monitoring, public security governance and smart city infrastructure construction.

Urban Science doi: 10.3390/urbansci10060324

Authors: Md Mamun Ur Rashid Jiefeng Hu Md Alamgir Hossain Nima Amjady Syed Islam

The increasing integration of renewable energy sources, smart appliances, and distributed energy technologies has significantly increased the complexity of residential energy systems, necessitating advanced Home Energy Management Systems (HEMS). Optimization techniques play a critical role in achieving key objectives, including energy cost reduction, load balancing, minimizing the peak-to-average ratio, and enhancing user comfort. This paper presents a comprehensive review and critical analysis of optimization techniques employed in HEMS, including mathematical methods, metaheuristic algorithms, artificial intelligence (AI)-based approaches, and rule-based strategies. These techniques are systematically classified and compared based on scalability, computational complexity, uncertainty handling, and real-time applicability. The analysis reveals that while conventional methods provide reliable solutions for structured problems, AI-based techniques offer superior adaptability and performance in dynamic and data-driven environments. Furthermore, key research gaps are identified, including limited multi-objective optimization, inadequate consideration of uncertainty and electric vehicle integration, and the lack of real-world implementation. Finally, future research directions are outlined, emphasizing hybrid optimization frameworks and intelligent, IoT-enabled energy management systems.

Urban Science doi: 10.3390/urbansci10060323

Authors: Konstantina Pyrgaki Maria Margarita Ntona Suraj Kumar Bhagat

Groundwater quality assessment in urban and peri-urban environments is often constrained by incomplete monitoring records, irregular sampling frequencies, and heterogeneous environmental datasets. The primary objective of this study is to predict the Water Quality Index (WQI) in the Attica River Basin, Greece, using advanced machine learning (ML) techniques. A groundwater quality dataset comprising 958 observations from 80 monitoring stations was analyzed using six physicochemical parameters, namely electrical conductivity, ammonium, nitrate, nitrite, chloride, and sulphate. Three modeling approaches, namely TabNet (with Winsorization), SVM, and Gradient Boosting Machines (GBM), were implemented to estimate groundwater quality conditions. To address the challenge of missing data, Multiple Imputation by Chained Equations (MICE) with Predictive Mean Matching (PMM) was implemented and systematically compared against conventional imputation approaches, including smoothed averages, interpolation, and forward-fill methods. The novelty of this study lies in the integration of open-access groundwater chemistry data, advanced multivariate imputation (MICE-PMM), and attention-based deep learning (TabNet) for groundwater quality prediction in a Mediterranean peri-urban area under data-scarce conditions. Using a multi-year groundwater monitoring dataset, the results indicate that the integrated MICE-PMM and TabNet framework achieved the highest predictive performance, with R2 = 0.91, NSE = 0.91, RMSE = 52.21, and MAE = 25.68. Feature importance and sensitivity analyses identified nitrate as the dominant driver of WQI variability, highlighting the strong influence of anthropogenic nutrient loading on groundwater quality. Overall, the proposed framework provides a transferable, data-driven approach for groundwater quality prediction, environmental monitoring, and groundwater resource management in urban and peri-urban aquifer systems characterized by incomplete environmental datasets.

Urban Science doi: 10.3390/urbansci10060322

Authors: Alexandra del Rosario Moncayo Vega Jessica Andrea Ordóñez Cuenca Victor Hugo Yanangomez Leiva

In the context of economic disparities, housing as a fundamental right highlights processes of social differentiation and stratification. From a complexity perspective, factors such as location, distance from development hubs, and designs that standardize needs exacerbate weaknesses in its conception. The new realities of living in housing prompt us to rethink design approaches that integrate housing and work. This research analyzes the Ciudad Alegría Social Housing Program, located in the city of Loja, Ecuador. The diagnostic method indicated that 24% of homes have commercial projections as a survival strategy. While these spatial patterns diminish the levels of habitability in the homes, they also provide benefits such as proximity between home and work, savings in transportation costs, interaction with neighbors, and mixed uses. These observations reveal gaps in the architectural design process, which fails to consider both service providers and users in decision-making related to the design of VIS programs, highlighting the need for this phenomenon to be elevated to public policy.

Urban Science doi: 10.3390/urbansci10060321

Authors: Emad Noaime Maan Chibli Lamia Hakim Zeinab A. M. Elhassan

Post-war reconstruction in Aleppo requires more than replacing damaged buildings; it demands an understanding of the city’s historically layered urban fabrics, their differing socio-spatial logics, and their unequal capacities for recovery. Following severe conflict-related destruction during the Syrian civil war, particularly between 2012 and 2016, and the additional impact of the February 2023 earthquake, Aleppo’s recovery is further complicated by the heritage significance of its Ancient City, inscribed on the UNESCO World Heritage List in 1986 and included on the List of World Heritage in Danger since 2013. This study examines how urban morphology can guide reconstruction through a comparative analysis of four neighborhoods representing major phases of Aleppo’s development: Jdaideh, Azizieh, Mohafaza, and Jabal Badro. Using a qualitative historical–morphological approach, the research analyzes figure–ground relations, street-network structure, degrees of transition between public, semi-public, semi-private, and private spaces, and landmark–node systems to identify the spatial characteristics, temporal persistence, and planning meaning of each district. The findings show that Aleppo is not a homogeneous urban system but a city composed of distinct fabrics with different strengths, vulnerabilities, and reconstruction needs. The comparison further demonstrates that density alone is not an adequate indicator of urban quality or resilience. The study concludes that reconstruction should be based on fabric-specific strategies, including preservation-sensitive rehabilitation, reinforcement of public nodes, balanced connectivity, governance-aware phasing, and incremental upgrading. Urban morphology is therefore proposed as a practical, but not exhaustive, framework for context-sensitive recovery in conflict-affected and historically layered cities.

Urban Science doi: 10.3390/urbansci10060320

Authors: Ali Soltani Hamed Najafi Kashkooli Andrew Allan

Urban sprawl in Iran has previously been examined through spatial measurement, driver classification, and multi-criteria weighting approaches. However, less attention has been given to the hierarchical structure through which governance, market, infrastructure, demographic, and regulatory conditions reinforce one another over time. This study develops a structural interpretation of urban sprawl in Iran’s major metropolitan regions by integrating expert refinement of key drivers with Interpretive Structural Modeling and MICMAC analysis. Rather than ranking drivers by relative importance, the analysis identifies their causal positioning within the wider sprawl system. The findings show that institutional fragmentation, weak enforcement capacity, and limited metropolitan coordination occupy the deepest structural levels, shaping downstream outcomes such as speculative land development, infrastructure-led peripheral expansion, housing pressure, and the growth of outlying settlements. The study contributes to urban-sprawl scholarship by reframing Iranian metropolitan expansion as a governance-embedded spatial process and by identifying leverage points for coordinated intervention. Policy responses should therefore prioritize institutional alignment, enforceable growth-management mechanisms, and infrastructure investment that supports compact rather than dispersed metropolitan development.

Urban Science doi: 10.3390/urbansci10060319

Authors: Sara Qwaider Mohammad Sharif Zami Ahmed Abdelqader Mashal Hamed Alammar Turki Ibrahim

The Saudi Green Initiative (SGI) represents a major national effort to enhance environmental sustainability and urban livability in Saudi Arabia. Despite its ambitious targets, limited empirical research has evaluated its spatial performance and social impacts. This study assesses the progress of SGI implementation in Riyadh by examining the spatial distribution, accessibility, and equity of urban green spaces (UGS), alongside residents’ perceptions of their quality. A mixed-methods approach was adopted, integrating Geographic Information Systems (GIS)-based spatial analysis with a structured survey of 180 residents. Spatial indicators were evaluated against the World Health Organization (WHO) benchmark of 9 m2 per capita and the SGI target of 28 m2 per capita. The results reveal that although total green space has increased between 2018 and 2024, its distribution remains uneven, with high-density neighborhoods consistently falling below recommended standards. Survey findings indicate high satisfaction with recreational and environmental benefits, but lower satisfaction with facilities and public engagement. The study highlights that increasing total green space alone does not ensure equitable access and emphasizes the need for population-sensitive planning strategies. These findings provide practical insights for improving the spatial equity and effectiveness of urban greening initiatives and contribute to broader sustainable urban development goals.

Urban Science doi: 10.3390/urbansci10060318

Authors: Emad Noaime Maan Chibli Lamia Hakim

Post-war Aleppo is often framed through destruction, legal constraints, and the technical demands of reconstruction. This article challenges that assumption by re-reading Aleppo’s pre-2011 municipal vision as an analytical resource for post-war recovery. The study adopts a qualitative interpretive methodology based on municipal archival material, including the City Council work programme, strategic planning presentations, project documents, and materials related to the City Development Strategy, Madinatuna initiative, the old city, Bab Antakiya, and major public-space and service initiatives. The analysis followed three steps: identifying repeated municipal priorities and planning concepts; organizing them into thematic axes; and interpreting flagship projects as spatial expressions of a broader municipal vision. To assess post-war relevance, the archive is also read against evidence of damage, displacement, urban functionality, and heritage loss. The results show that Aleppo’s pre-2011 municipal vision can be reconstructed through six interrelated axes: strategic urban development and managed growth; the old city as a living urban fabric; urban repair in the city centre; mobility and accessibility; culture and social development; and development partnerships and international cooperation. The findings reveal that these axes formed a partially integrated municipal urbanism rather than isolated projects, while flagship interventions such as Bab Antakiya, the Green Path, the river corridor, and the Citadel surroundings materialized this logic. The study also finds that this vision remained institutionally vulnerable because of political centralization and limited municipal autonomy. It concludes that post-war recovery should build on critical continuity rather than reconstruction from scratch.

Urban Science doi: 10.3390/urbansci10060317

Authors: Soojin Kim Jeonghee Lee Sugwang Lee

National Forest Trails (NFTs), a key component of forest welfare infrastructure, increasingly require a shift from government-led management to citizen-participatory governance. This study examined the structural relationships among volunteer motivation, activity satisfaction, perceived quality-of-life (QoL) change, and behavioral intention in the context of NFT volunteering. A survey was conducted with 217 adults who had participated in forest trail volunteering programs in Korea, and the data were analyzed using structural equation modeling (SEM). The results showed that volunteer motivation had significant positive effects on reward importance, activity satisfaction, and perceived QoL change. Activity satisfaction positively influenced both Future Participation Intention and Active Participation Intention, whereas perceived QoL change had a significant positive effect only on Active Participation Intention. In addition, activity satisfaction and perceived QoL change mediated the relationship between volunteer motivation and Active Participation Intention. These findings suggest that forest trail volunteers are not merely supplementary labor for trail management, but active participants in forest governance who both contribute to and benefit from the environments they help sustain. Overall, the study indicates that sustainable NFT volunteering depends not only on motivation itself, but also on the quality and personal meaning of the volunteer experience. The findings highlight the importance of experience-centered program design, appropriate recognition systems, and greater attention to participant-centered well-being outcomes in sustainable forest trail governance.

Urban Science doi: 10.3390/urbansci10060316

Authors: Diego Julian Rodriguez Patarroyo Jaime Francisco Pantoja Benavides Frank Nixon Giraldo Ramos

This work proposes a spatial optimization framework based on Monte Carlo Tree Search (MCTS) to support infrastructure planning in complex urban environments. The challenge lies in integrating diverse geospatial and socioeconomic data to balance efficiency, defined as potential demand, with territorial equity, related to mobility needs. The approach formulates the problem as a sequential decision process, capturing the interdependence of location choices and enabling structured exploration of the solution space. Unlike traditional optimization methods that rely on local heuristics or require strong simplifications, this framework accommodates non-linear relationships and competing objectives without sacrificing system complexity. The use of MCTS effectively balances exploration and exploitation, making it well-suited for high-dimensional, non-convex spatial problems. This methodology offers a flexible and scalable tool for urban planning, adaptable to various contexts and constraints. It supports generating solutions that are both efficient and aligned with equity considerations, providing valuable guidance for decision-making in rapidly evolving urban systems.

Urban Science doi: 10.3390/urbansci10060315

Authors: Valeria Saiu Matteo Mocci

This study introduces RE-VAL (REal-estate VALuation), an explainable framework for urban real-estate analysis that integrates reproducible data acquisition, geographically informed feature processing, predictive benchmarking, and interpretable outputs suitable for decision-support-oriented analysis. Unlike static automated valuation models, the RE-VAL framework is designed to reflect context-dependent market behaviour across heterogeneous urban areas. The comparative evaluation on 1153 residential listings from Cagliari (Italy) showed that MLP achieved the strongest predictive performance, while Random Forest provided the most convincing balance between predictive competitiveness and interpretability. Beyond point estimation, the framework leverages SHAP-based decomposition to translate algorithmic outputs into transparent, monetary-based “Bonus/Malus” adjustment tables. The analysis highlights the presence of potentially non-linear interactions, including a possible premium associated with energy efficiency in prestigious areas, and suggests that the framework can remain informative when incomplete technical data are preserved as potential proxy signals rather than being discarded as noise. Rather than identifying a single predictor, RE-VAL provides a transparent, extensible and decision-oriented workflow for urban real-estate valuation, advancing the integration of explainable artificial intelligence within complex spatial-economic systems.

Urban Science doi: 10.3390/urbansci10060314

Authors: Todd Gardner

This study introduces a multi-source spatial methodology that moves beyond the traditional urban/rural dichotomy to classify the American landscape into detailed, temporally defined settlement types. By combining historical housing unit and population estimates (HHUUD10 and LTDB) standardized to 2010 census tract boundaries with high-resolution, grid-level data on the built environment (HISDAC-US), this research establishes a settlement typology based on the development history of detailed geographic units. This framework classifies areas (from Prewar Cores and 21st-Century Suburbs to exurban fringes, outlying towns and rural areas) based on their era of development and proximity to urban centers. Applying this typology reveals profound spatial and demographic decentralization spanning eighty years of metropolitan expansion. The findings demonstrate a stark geographic sorting: expanding greenfield edges and exurbs have become magnets for high-income, highly educated, and predominantly White populations. However, longitudinal tracking reveals a distinct morphological “life-course” within suburban rings. As older suburbs age and their housing stock depreciates, they open to wider demographic integration, transforming into destinations for Black and foreign-born residents. Furthermore, the data highlight a contemporary polarization of human capital, concentrated in both the newest suburban peripheries and the resurgent urban cores, contrasting with persistent economic decline in outlying towns and rural areas. Ultimately, this methodology provides a flexible, longitudinal framework for understanding the long-term morphological and demographic evolution of American settlement.

Urban Science doi: 10.3390/urbansci10060313

Authors: Manuel Wolff Benjamin Labohm Dagmar Haase

In an increasingly urbanized world, ensuring equitable access to urban green spaces (UGS) is essential for human well-being. Previous studies have largely focused on measuring proximity or availability of UGS, often neglecting the role of the walkable environment and the interaction between supply, demand, and movement flows. To address this gap, we develop a novel modeling framework that integrates the Detour Index (DI) and Local Significance (LS) to jointly capture physical barriers and recreational flows within urban street networks. Using openly available data from OpenStreetMap and Urban Atlas, we model the walkable environment in Leipzig, Germany, at a high spatial resolution. The approach enables the identification of inefficient routes, potential barriers, and areas of high use intensity, providing actionable insights for urban planning. By combining network-based accessibility with flow-based indicators, our method advances existing approaches that rely on static distance measures. The analyses of different planning alternatives further demonstrate how changes in urban structure affect accessibility and crowding patterns. The framework is transferable and based on open data, providing a foundation for future research to integrate behavioral factors and richer datasets to further refine accessibility modeling.

Urban Science doi: 10.3390/urbansci10060312

Authors: Kostadin Kostadinov Angel M. Dzhambov Angel Burov Marco Helbich Iana Markevych Mark J. Nieuwenhuijsen Donka Dimitrova

Background: Translating urban environmental health evidence into actionable policies remains challenging in South-Eastern Europe, where environmental epidemiology has yet to reach maturity and institutional capacity and cross-sector coordination are suboptimal. This study assessed stakeholders’ awareness, perceived roles, and prioritization of urban health challenges, alongside the barriers and evidence needs related to healthy and sustainable urban development. Methods: A cross-sectional online survey was conducted between March and May 2025 among 108 stakeholders identified through a collaborative evaluation process. Participants represented national institutions, municipal actors, academia, non-governmental organizations, business, and citizens. They reported on their role and influence, and were asked to identify priority urban health problems, relevant policies and actions, perceived barriers to decision-making, and expected benefits of addressing priority problems. Results: Most respondents reported limited or moderate influence on urban decision-making. Priority problems clustered around air pollution, traffic, and land-use pressures, with climate change and heat also frequently cited. Dominant barriers included lack of coordination and policy continuity, insufficient political support, and limited funding and institutional capacity. Anticipated gains centered on improved public health, cleaner air, and citizen satisfaction, with broader quality-of-life and economic co-benefits also identified. Conclusions: Prioritized urban environmental problems are largely consistent with scientific evidence on their health impacts, though certain risk factors remain underestimated. Access to specific, actionable scientific evidence and the co-production of solutions with broad stakeholder representation are essential prerequisites for effective urban health policy and practice.

Urban Science doi: 10.3390/urbansci10060311

Authors: Aleksandra Milovanović Mladen Pešić Stefan Janković Milica Milojević Jelena Ristić Trajković Verica Krstić Ana Nikezić Vladan Djokić

This study investigates whether spa settlements can be analytically interpreted through a relational spascape framework that reveals structural and configurational patterns beyond conventional typological classifications. In the context of increasing interest in therapeutic landscapes and heritage-sensitive development, spa settlements represent complex spatial systems shaped by the interplay of natural resources, urban form, and socio-cultural practices, yet they remain insufficiently understood through existing analytical models. The methodology is based on a structured analytical design combining three urbanization dimensions (material transformation, territorial regulation, and everyday life) with six thematic fields, operationalized through graded cross-affiliation scoring. The empirical research is conducted on a sample of 12 spa settlements in Serbia, selected to reflect diverse geographical, morphological, and developmental conditions. Statistical calibration was performed using Principal Component Analysis (PCA) and hierarchical clustering to identify underlying structural relationships and configurational groupings. The results indicate that spa settlements operate as multi-affiliated relational entities rather than fixed typologies, exhibiting dimension-specific structural logics and forming distinct configurational families depending on the analytical perspective applied. PCA reveals differentiated internal structures across dimensions, while clustering confirms the absence of a single stable typology. The findings support a relational understanding of spa settlements as dynamic spatial systems characterized by shifting alignments of material, regulatory, and experiential factors. Beyond the Serbian context, the study offers a transferable methodological framework that connects qualitative urban interpretation with quantitative spatial analysis, contributing to heritage-sensitive planning, territorial governance, and the management of spa systems as relational clusters.

Urban Science doi: 10.3390/urbansci10060310

Authors: Jose Marin Pedro V. Mauri María del Pilar Garcia de Paredes Ana Centeno Lorena Parra

In recent years, the use of warm-season species, which are species requiring less water, has been pursued in continental areas, but their dormancy and spring green-up need to be properly defined. In urban green areas, we find that small-scale microclimatic differences, while less intense than classical urban–rural gradients, still influence vegetation performance and spring green-up. This study examines the impact of microclimatic temperature variation on the spring green-up of different cool-season and warm-season turfgrasses in the continental climate of Madrid, Spain. The evaluation of colour change during the spring green-up process has been conducted using different vegetation indices, and mathematical models for correlating temperature with the indices’ values have been obtained. The results indicate that with average temperatures varying by about 1.3 °C and 0.9 °C in January and February, respectively, there have been marked differences in spring green-up, especially in cool-season turfgrasses, of almost one month. In contrast, differences in warm-season turfgrasses were reduced. Among the four vegetation indices, Canopeo has proved to be the best for detecting the early stages of spring green-up, with R2 values ranging from 0.43 to 0.92. Meanwhile, the tailored greenness index for turfgrass was the most effective for determining the moment at which warm-season grasses achieve the colouration of cool-season grasses, with R2 ranging from 0.79 to 0.85. Finally, the green leaf index was particularly valuable for identifying differences among species and sectors throughout the entire spring green-up process. Models based on this index achieve high R2 values (0.57 to 0.94), but these models predict the moment at which warm-season grasses achieve cool-season grasses’ colouration later than it actually occurs. Understanding how turfgrasses respond to these localised microclimatic conditions is essential for selecting resilient species and improving maintenance strategies in parks, sports areas, and other components of urban green infrastructure.

Urban Science doi: 10.3390/urbansci10060309

Authors: Chiranjib Chaudhuri

Fragmented transit governance across multiple agencies makes measuring service inequality in large metropolitan regions notoriously difficult. This paper maps schedule-aware transit service intensity—an origin-side, supply-focused component of accessibility—across the Greater Toronto Area (GTA) by integrating General Transit Feed Specification (GTFS) data from six providers within an H3 hierarchical hexagonal grid. The measure does not capture destination access, travel time, transfers, fares, reliability, or crowding, and is therefore framed throughout as a service-intensity indicator rather than a full accessibility evaluation. We operationalize the indicator as the number of cumulative scheduled departures per hour reachable within an 800 m walking catchment for three distinct time windows: weekday peak, weekday midday, and Saturday midday. Across 9635 hexagons and 23,026 stops, our results reveal a sharply hierarchical regional network. When weighted by population, 16.4% of GTA residents have no scheduled service within walking distance during the weekday morning peak; the corresponding area-weighted share, reflecting the extensive greenbelt and agricultural fringe, is 70.6%. Only 22.6% of hexagons reach at least 12 departures per hour, while 75.5% of residents meet that threshold. Median service intensity drops from 234.25 departures per hour in the Urban Core to zero beyond the Inner Suburban Ring, and service thins out on weekends, with retention in the outer rings dropping to roughly 75% of weekday levels. Spearman correlations show that service intensity is concentrated in denser, more diverse, and lower-income census-tract contexts, with population density emerging as the strongest hex-level correlate (ρ=0.69); after Clifford–Richardson correction for spatial autocorrelation (effective n≈745), the principal CT-level correlations remain statistically significant (p<10−15), and partial correlations controlling for density indicate that socioeconomic composition retains an independent, if attenuated, association. Under one-tract-one-observation aggregation (n=1144 unique tracts), the income gradient strengthens to ρ=−0.74 and becomes co-equal in magnitude with population density (ρ=0.74), confirming that the hex-level coefficients are not artifacts of pseudo-replication. A population-weighted Gini coefficient of 0.60 confirms substantial distributional inequality. Sensitivity analyses confirm that the Inner-to-Outer Suburban break is robust to alternative ring thresholds (10/25/40 and 20/35/50 km), to exclusion of the four Halton municipalities affected by incomplete local-feed coverage, to H3 resolution at the municipal level, and—in a representative shortest-path network sub-analysis for Pickering (not a full GTA-wide network-distance test)—to use of network rather than Euclidean walking distance. These patterns suggest that a substantial gap exists between where suburban residential growth has occurred and where frequent transit service is available, a pattern with historical roots in the 1996–2006 service–need alignment, though the 2006–2023 trajectory is not directly measured here. The results suggest that the transition zone between the inner and outer suburbs may warrant further investigation as a planning focus, and that cross-agency weekend service coordination merits further analysis as a potential equity dimension. This multi-agency H3 framework establishes a reproducible baseline for monitoring schedule-aware service intensity in polycentric metropolitan areas.

Urban Science doi: 10.3390/urbansci10060305

Authors: Jurgis Zagorskas Zenonas Turskis

The integration of renewable energy technologies into urban buildings is a key strategy in sustainable city development. This study explores the application of building-integrated photovoltaic (BIPV) systems in a selected building at Vilnius Gediminas Technical University (VGTU), aiming to identify the most balanced solution among energy efficiency, architectural quality, and operational feasibility. Using a Building Information Model (BIM) of the existing structure, five alternative design scenarios were developed by varying the number and capacity of façade-mounted photovoltaic (PV) panels and semi-transparent PV windows. Each scenario was evaluated against six criteria: (1) potential solar energy yield, (2) temporal correlation between energy generation and building consumption, (3) maintenance accessibility and associated cost, (4) architectural aesthetics, (5) installation cost, and (6) cost effectiveness. To ensure a rigorous and interdisciplinary evaluation, the Delphi-based ELECTRE Multi-Criteria Decision-Making (MCDM) method was applied. Expert panels representing disciplines of construction engineering, architecture, electrical engineering, and business management participated in determining the relative importance of each criterion. The results demonstrate the potential of combining BIM-based energy simulation with expert-driven decision analysis to optimize BIPV integration strategies in complex urban environments. The proposed framework offers a replicable methodology for guiding sustainable façade design and supporting the adoption of renewable energy in various public and administrative buildings across cities.

Urban Science doi: 10.3390/urbansci10060308

Authors: Sommai Khantong Charuay Savithi Mohammad Nazir Ahmad

Smart cities generate vast, heterogeneous data streams from transportation networks, energy grids, environmental sensors, and public services, yet the semantic fragmentation of these data silos prevents urban operators from deriving actionable, cross-domain intelligence. Knowledge graphs (KGs) have emerged as a powerful paradigm for integrating diverse, large-scale data collections through graph-based representations of entities and their relationships. This paper applies the Design Science Research Methodology (DSRM) to design, develop, and evaluate UrbanKG, a layered artifact that deploys knowledge graphs as the semantic backbone of smart city data infrastructure. We demonstrate the framework through a proof-of-concept implementation using publicly available urban datasets across five domains, yielding a 287,000-triple knowledge graph validated through cross-domain SPARQL queries and accessibility analysis. Following the six DSRM process steps—problem identification, objective definition, design and development, demonstration, evaluation, and communication—the framework addresses ontology design, multi-source data fusion, federated governance, temporal reasoning, and hybrid deductive–inductive inference. The artifact satisfies all five design objectives and contributes four transferable design principles. Six open research challenges are identified as the forward research agenda.

Urban Science doi: 10.3390/urbansci10060307

Authors: Chrystala Psathiti Nadia Charalambous

Architectural, urban design, and planning practices are increasingly expected to demonstrate measurable impact, accountability, and responsiveness to complex environmental and social challenges. Evidence-based design (EBD) and research-informed design (RID), which ground design decisions in systematically gathered and critically evaluated knowledge, offer a structured pathway to bridge research and practice. Despite growing recognition, however, EBD and RID remain unevenly integrated across professional practice, particularly within small and medium-sized enterprises (SMEs), which constitute the majority of firms in Europe. This paper explores how SMEs understand, adopt, and operationalize research within architectural, urban design, and planning processes, while identifying the factors that enable or constrain the integration of research into practice. Drawing on a qualitative multiple-case study of four European firms located in Cyprus, Portugal, Italy, and Croatia the study uses semi-structured interviews and thematic analysis supported by AI-assisted coding to identify patterns in how systematic research is understood, enacted and positioned in everyday SME practices. The findings show that research integration depends less on firm size than on the interplay between client expectations, organizational culture, and professional ideology. Practices span a spectrum ranging from ad hoc, compliance-oriented, and project-specific inquiry to strategically embedded and, in one case, activist research-led modes. While research engagement can enhance credibility, efficiency, and innovation, persistent barriers—including limited resources, client resistance, deficient knowledge-management routines, and the absence of shared evaluative frameworks—continue to hinder systematic adoption. Building on the cross-case analysis, the paper proposes a conceptual framework of different modes of research integration in SMEs, offering a heuristic lens for understanding how organizational and contextual factors shape the uptake of research in design practice. The findings contribute to ongoing discussions on practice-based research and highlight the need for more context-sensitive approaches to research integration in small and medium-sized design firms.

Urban Science doi: 10.3390/urbansci10060306

Authors: Gabriel Dadashev Alina Zukin Francisco Camara Pereira Bat-Hen Nahmias-Biran

For decades, transportation planning has relied on utilitarian principles, which aim to maximize cumulative benefit by meeting the needs of the “average user.” This approach ignores fundamental differences between population groups and produces uniform solutions that fail to address the diverse needs of women, children, the elderly, and other disadvantaged populations. In response, there are growing calls for a transportation justice paradigm that emphasizes individuals’ ability to access meaningful opportunities according to their characteristics, abilities, and life circumstances. Autonomous Mobility on Demand (AMoD) holds the potential to transform future transportation systems. However, without deliberate planning, they risk replicating existing patterns of inequality for populations whose mobility needs differ from those of the average user. This study applies transportation justice principles to examine how AMoD systems can be designed to meet diverse user needs. Using a combination of an Autoencoder for learning reduced representations and an HDBSCAN clustering algorithm, the analysis identifies distinct travel patterns across socioeconomic groups. These findings reveal significant gaps between population segments, particularly among children and older adults, and demonstrate how AMoD systems could expand access to after-school activities, reduce social isolation among elderly women, and reduce various transportation-related social gaps by improving their ability to reach a wider range of opportunities.

Urban Science doi: 10.3390/urbansci10060303

Authors: Dongyue Zhao Qian Chen Yuyou Yao Yunhe Tong

Emergency response in urban gas pipeline networks is highly sensitive to stochastic traffic conditions, which introduce substantial uncertainty in crew travel times to leakage sites. Existing facility location models typically rely on predefined candidate sites and deterministic travel assumptions, limiting their ability to capture full-cycle dynamic recovery processes under random leakage events and traffic congestion. This study develops a candidate-free location optimization framework for repair station siting under stochastic road resistance conditions, aiming to characterize spatial variability in emergency response capability. The framework integrates a candidate-free facility location model with a hybrid greedy–Monte Carlo solution strategy to optimize station layouts across network-wide stochastic scenarios. Coverage reliability, response time, and construction cost are jointly considered to support robust siting decisions. A case study based on the real road and gas pipeline networks of City H demonstrates the effectiveness of the proposed approach. Across 20,000 stochastic road resistance scenarios, the optimized layout achieves an average service coverage rate of 97.77% within the specified response time threshold, while maintaining stable performance under variability. Although increasing the number of stations enhances response capability, the improvement exhibits clear diminishing marginal returns. These findings provide quantitative guidance for determining cost-effective station scale and prioritizing core hub locations under uncertainty. The proposed framework offers a structured decision-support tool for resilience-oriented planning, prioritization of critical segments, and evaluation of emergency response and maintenance strategies in urban gas pipeline systems.

Urban Science doi: 10.3390/urbansci10060304

Authors: Andrea Goyes-Balladares Concepción López-González Roberto Moya-Jiménez Mario Rivera-Valenzuela Daniel Dávila-León Andrea Villalobos-Pozo Carolina Obando-Navas Bolívar Chávez-Ortiz

Walkability has traditionally been assessed through physical indicators and objective metrics of the built environment; however, persistent methodological fragmentation limits its interpretive capacity in complex urban contexts. This article proposes an operational analytical framework for the analysis of walkability in Latin American intermediate commercial cities, understood as a relational and multiscale urban condition. The study adopts a qualitative–analytical design based on a systematic literature review and the comparative analysis of seven international walkability assessment methodologies. Through this critical synthesis, a framework is constructed that integrates macro, meso and micro scales, differentiated analytical domains, and a sequential interpretative procedure. The main contribution lies in providing an analytical structure that enables coherent interpretation of the tensions between urban structure, socio-economic functioning and pedestrian experience, avoiding reductive or decontextualized readings of walking in intermediate commercial cities.

Urban Science doi: 10.3390/urbansci10060302

Authors: Md Ashikuzzaman Yongze Song Atiq Uz Zaman

Dhaka, one of the world’s most densely populated megacities, has faced a severe ecological decline, with green cover plummeting from 44.80% in 1975 to approximately 24.50% by 2005. In response, urban rooftop farming has emerged as a vital adaptation strategy to mitigate the urban heat island effect and air pollution. Objective: This study evaluates the transition from “pixels to policy” by testing automated identification methods for URF to support evidence-based urban governance, specifically the 10.00% holding tax rebate offered by the Dhaka North City Corporation. Utilizing high-resolution (3 cm) drone imagery across three diverse areas of interest—representing planned, organic, and mixed-use urban fabrics, the research compares the performance of Support Vector Machines, U-Net, and Text-Segment Anything Model. Accuracy was validated using a confusion matrix based on 1000 randomly stratified sample points. The SVM model emerged as the most reliable, achieving a Kappa index of 0.74 and 100.00% user accuracy for identifying rooftop vegetation, significantly outperforming the U-Net model (Kappa 0.14). Spatial analysis quantified a distinct “green divide,” revealing that while planned residential zones achieved over 7.50% rooftop greening coverage, dense organic settlements were limited to 6.00%. The study concludes that high-accuracy SVM-based identification provides a scalable foundation for automating fiscal incentives. To bridge the socio-spatial green divide, policy interventions must shift toward inclusive greening strategies, such as vertical farming, and formal integration of URF into Dhaka’s blue-green infrastructure networks.

Urban Science doi: 10.3390/urbansci10060301

Authors: Sara El-Sayed Gabr Mamdouh Y. Saleh Ahmed H. Ibrahim Hossam Wefki

Investment in infrastructure is considered the foundation for economic growth. However, traditional construction and maintenance methods in Egypt are carbon-intensive, which conflicts with sustainability strategies. Therefore, there was a need to develop a model for evaluating highway maintenance methods to facilitate decision-making on the best ones, economically, environmentally, and socially. This study included a model for evaluating sustainability in road maintenance. It integrated carbon management and value engineering to facilitate the selection of the best alternatives for achieving sustainability. The literature on sustainability criteria covering the project life cycle was consulted, and 27 key factors across the three sustainability criteria were selected. A questionnaire was conducted to determine the weights of the criteria using the Analytic Hierarchy Process (AHP). Road maintenance scenarios were then developed, and the carbon emissions for each were calculated. The cost of carbon disposal was added to the project life cycle cost using CCS technology. This model was named SRMVE because it ultimately combines economic and environmental challenges into a single factor to facilitate a comparison of the proposed alternatives and achieve the best degree of sustainability. The model results were compared with the sustainability scores generated by the AHP to assess the extent of agreement. This model provides decision-makers with a way to sort through maintenance alternatives and identify those with the lowest lifecycle emissions while maintaining the service and safety levels.

Urban Science doi: 10.3390/urbansci10060300

Authors: Nawal Louzi Mahmoud AlJamal Mohammad Q. Al-Jamal

Urban traffic accidents emerge from complex interactions among traffic instability, roadway structure, environmental disturbance, and temporal dynamics, yet many existing prediction approaches still treat accident risk as a discrete classification problem over isolated observations. This study proposes a Continuous Hazard Field Intelligence Framework for Traffic Accident Emergence and Urban Safety Prediction, which models hidden urban danger as a topology-aware spatio-temporal hazard field that evolves continuously across connected transportation infrastructure. The framework integrates heterogeneous urban traffic observations, including incident records, crash data, roadway attributes, temporal cues, and contextual risk factors, into a unified hazard-aware learning pipeline. A dedicated preprocessing strategy combines topology-constrained spatial alignment, temporal hazard window embedding, risk-diffusion feature lifting, hazard-sensitive normalization, and continuous hazard surface initialization to convert fragmented event-centered observations into a smooth and learning-ready hazard representation. A structured deep learning architecture is then developed to perform spatial hazard encoding, temporal hazard evolution, continuous hazard reconstruction, and localized accident emergence prediction. Experimental evaluation was conducted on two large-scale real-world traffic safety datasets, namely the XTraffic Incident Dataset (2022–2024) with 1,441,904 records and the Motor Vehicle Collisions–Crashes Dataset with 2,026,647 records. All model configurations were evaluated under the same experimental setting, using the same dataset-specific preprocessing protocol, a 70/30 train–test split, and identical evaluation metrics. The final CHFI configuration achieves 99.12% accuracy, 98.94% precision, 98.76% recall, 98.85% F1-score, and 0.998 AUC on Dataset 1, and 98.63% accuracy, 98.41% precision, 98.16% recall, 98.28% F1-score, and 0.997 AUC on Dataset 2. Compared with the initial non-hazard-aware baseline configuration evaluated under the same data split and evaluation protocol, the final CHFI model improves the F1-score by 7.91 percentage points on Dataset 1 and 8.26 percentage points on Dataset 2. These results indicate that the proposed hazard-field formulation can improve accident-emergence prediction within the controlled experimental setting, while the reported gains should be interpreted relative to the specified baseline and evaluation design.

Urban Science doi: 10.3390/urbansci10060299

Authors: Havi Livne Efrat Blumenfeld-Lieberthal

Shared residential yards constitute a substantial yet often overlooked component of open space in dense cities. While their ecological significance has been demonstrated locally, less is known about how their morphological characteristics relate to estimated vegetated potential across metropolitan residential fabrics and how this potential is affected by urban renewal. This study addresses this gap through a typological analysis of shared residential yards in the Tel Aviv metropolitan area, Israel. Building on prior field-based research in Givatayim, the analysis was extended to five additional cities. Using GIS, residential environments were classified by building type and lot size category, and analyzed in relation to prevalence, Potentially Vegetated Area (PVA), chronological development, spatial clustering, and maintenance regimes. PVA is used here as a proxy for vegetated potential and as an indicator of spatial conditions associated with plant diversity and species richness. The findings show that the typological framework captures most shared residential areas. Several typologies account for a substantial share of estimated PVA, indicating higher vegetated potential and spatial conditions associated with biodiversity-supporting functions. Yet many buildings with relatively high estimated vegetated potential are older than 45 years and thus more likely to be exposed to redevelopment pressure. Estimated vegetated potential varies in relation to typological distribution, spatial clustering, management dynamics, and chronological exposure to renewal. Thus, we argue that shared residential yards should be recognized as a distributed ecological resource whose transformation cannot be addressed effectively through parcel-based planning alone.

Urban Science doi: 10.3390/urbansci10060298

Authors: Gabriel Joseph Isibor Timea Bezdan Gordana Jovanović Nataša Radić Svetlana Stanišić Nenad Stanić Andreja Stojić Mirjana Perišić

Benzene is a major carcinogenic urban pollutant whose variability reflects interactions between emission sources, human activity, and atmospheric conditions. Although COVID-19 restrictions generally reduced traffic-related emissions, the combined effects of mobility changes, residential activity, and policy interventions on urban benzene dynamics remain insufficiently understood. This study investigated benzene variability in Belgrade, Serbia, during the COVID-19 state of emergency, from 15 March to 6 May 2020. A multi-source dataset was used, integrating high-resolution VOC measurements by PTR-quad-MS, meteorological variables, regulatory air-quality indicators, epidemiological data, mobility proxies, and quantified government-response measures. Tree-based ensemble machine-learning models, metaheuristic hyperparameter optimization, and explainable artificial intelligence methods, including SAGE and SHAP, were applied to examine non-linear and time-lagged relationships within the urban atmospheric system. The results showed that benzene variability was primarily associated with co-measured non-target VOCs, reflecting shared urban emission-source structures. Mobility and policy-related predictors contributed through short delayed responses, with an estimated response window of approximately 48–72 h. Sustained mobility reductions were associated with lower benzene concentrations, whereas increased residential activity partially offset traffic-related reductions. Within the Belgrade case study, these findings demonstrate the potential of interpretable machine learning to extract robust patterns from heterogeneous urban environmental datasets, while emphasizing the need for validation across additional cities and non-pandemic conditions before broader generalization.

Urban Science doi: 10.3390/urbansci10060297

Authors: Yolanda Gpe. Aranda-Jiménez Laura del C. Moreno-Chimely Paola Selene Vera-Martínez Miguel Reyna-Castillo

This study examines how institutional pressures influence the adoption of social sustainability practices in habitat systems within the construction sector. Drawing on Institutional Theory, the research analyzes the differentiated effects of coercive, mimetic, and normative pressures, as well as the mediating role of organizational awareness. Data were collected through a digital survey administered between February and March 2026 to 102 professionals linked to construction and habitat development projects in Mexico, including architects, civil engineers, valuators, and related specialists. The proposed model was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that coercive pressures constitute the only statistically significant institutional mechanism affecting organizational awareness (β = 0.310; p = 0.043), while mimetic and normative pressures do not exhibit significant effects. Furthermore, organizational awareness strongly explains the adoption of social sustainability practices (β = 0.739; p < 0.001), which, in turn, is strongly associated with sustainable habitat outcomes (β = 0.711; p < 0.001). The model achieved moderate predictive power, with R2 values of 0.449 for awareness, 0.546 for adoption, and 0.505 for sustainable habitat systems. The findings contribute to institutional theory by demonstrating that institutional mechanisms operate asymmetrically in emerging contexts and that organizational awareness functions as a key explanatory mechanism linking external pressures with sustainability outcomes. The study also provides practical implications for urban governance, regulatory design, and socially sustainable habitat planning.

Urban Science doi: 10.3390/urbansci10060296

Authors: Khoren Mkhitaryan Arevik Hovhannisyan Armenuhi Ordyan Hayk Harutyunyan Edgar Kirakosyan

This study examines the transformative role of digital and artificial intelligence (AI)-enabled public procurement systems in enhancing governance efficiency within smart city environments, with a specific focus on Yerevan, Armenia. As urban administrations increasingly adopt data-driven governance models and digital infrastructures, public procurement remains a critical yet underexplored domain for innovation in transition economies. Despite ongoing e-government reforms in Armenia, procurement systems continue to face challenges related to procedural inefficiencies, limited transparency, and institutional constraints. To address these challenges, the paper develops a Governance Efficiency Framework that integrates digitalization, AI capabilities, and multi-criteria decision-making principles to assess and optimize public procurement processes in urban settings. The framework incorporates key dimensions such as transparency, operational efficiency, accountability, and data integration, enabling a comprehensive evaluation of procurement performance. The empirical application of the framework to the case of Yerevan provides insights into the structural and technological determinants of procurement efficiency in a transition economy context. The findings indicate that while digitalization has contributed to improvements in transparency, significant limitations remain in efficiency and system integration. A scenario-based analysis further suggests that AI-enabled analytics, process automation, and digital procurement platforms have the potential to reduce administrative delays, enhance transparency, and support more strategic and evidence-based decision-making under assumed implementation conditions. By bridging the fields of public procurement, digital governance, and smart city research, this study contributes both theoretically and practically. It offers a structured and adaptable framework for policymakers and urban administrators seeking to modernize procurement systems and strengthen governance efficiency in evolving digital environments.

Urban Science doi: 10.3390/urbansci10060295

Authors: Hilal Çepni João de Abreu e Silva

This systematic literature review comparatively examines two largely parallel research streams: the 15-minute city (15MC) and neighbourhood satisfaction (NS), identifying their overlaps, divergences, and unresolved tensions. It combines a bibliometric analysis of two thematic corpora with an in-depth full-text synthesis of empirical studies, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting practices. The bibliometric results show a rapidly expanding 15MC field since 2020, centered on proximity, accessibility, and sustainability, while NS research has a longer tradition focused on subjective well-being and perceived neighbourhood experiences, including environmental comfort, social cohesion, safety, and neighbourhood quality. Across the literature, the synthesis shows that spatial proximity and measured accessibility are important but insufficient to explain NS without also considering service quality, environmental comfort, perceived safety, and social relations. The review highlights persistent gaps in linking objective accessibility metrics with subjective outcomes, as well as mismatches in neighbourhood definitions and spatial scales. It also identifies limited evidence on temporal dynamics, population heterogeneity, and the social effects of proximity planning, including gentrification and displacement. Building on five conceptual bridges, the review proposes an integrated framework connecting objective proximity-based planning conditions with subjective, social, and contextual determinants of neighbourhood satisfaction.

Urban Science doi: 10.3390/urbansci10060294

Authors: Darja Kubečková Kateřina Kubenková Marek Jašek

Industrial areas, which represent a specific type of urbanised area with an extremely high concentration of material reserves, can be considered key anthropogenic raw material reservoirs in the context of urban mining. Industrial areas, characterised by a high material density and a specific composition of structural systems, show extraordinary potential for providing secondary raw materials with high material and energy value. This increases the need for their systematic evaluation. The aim of the present study was to define the role of the selected industrial area as a strategic node for secondary raw material extraction, to identify the structure and quality of “urban deposits” in the selected location of the Ostrava–Karviná region (CZ), and to provide an analytical framework for its integration into circular planning processes. The methodological approach is based on a combination of pre-demolition audit, material flow mapping, spatial analysis, and structural element characterisation. It is becoming apparent that industrial areas have a high material density and contain significant amounts of recyclable metals, reinforced concrete elements, etc. These stocks are often concentrated in structural systems with predictable geometries, such as serial assembly prefabricated and steel frames, allowing for more accurate estimates of recoverable volumes. The results show that the incorporation of industrial areas into the process of urban mining can significantly reduce the consumption of primary raw materials, mitigate the environmental impacts associated with the extraction of raw materials, and, at the same time, promote the regeneration of industrial areas (or brownfields) through the planned decomposition of structures. The inclusion of urban mining in urban development strategies and the regeneration of industrial sites leads to the prediction that urban mining is one of the key elements for achieving a material-efficient and low-carbon urban environment.

Urban Science doi: 10.3390/urbansci10050293

Authors: Shuqi Zhang Huiyu Zhou Zihan Zhao

Does public transportation infrastructure expansion necessarily improve urban air quality? Using panel data from 168 Chinese cities, this study examines the impact of public transportation infrastructure development on air quality by applying GTWR (Geographically and Temporally Weighted Regression) models to capture spatial–temporal heterogeneity. Partial Dependence Plots (PDPs) are further employed to identify nonlinear relationships, alongside mechanism analysis. The results indicate that the effects of public transportation infrastructure on air quality are significant but highly heterogeneous across cities and over time. Transport development is associated with air quality through channels related to industrial transformation and agglomeration dynamics, with the latter showing a stronger relationship. Moreover, several key variables exhibit nonlinear relationships with identifiable threshold effects. These findings suggest that the environmental benefits of public transportation infrastructure are context-dependent rather than universal. This study provides a more comprehensive understanding of transport–environment linkages and offers policy insights for optimizing urban transport systems and promoting sustainable development.

Urban Science doi: 10.3390/urbansci10050292

Authors: Zubair Ali Raja Muhammad Mashhood Arif Nida Batool Sheikh

This study examines how tech-enabled municipal service delivery can generate a digital city dividend, measured as residents’ expected financial gains in urban context. The purpose is to identify the beliefs and enabling conditions that most strongly shape these expectations. We collected resident survey data and analysed the proposed model using PLS-SEM in SmartPLS. The reflective measurement model was evaluated for reliability and convergent validity (composite reliability; AVE) and for discriminant validity using both the Fornell–Larcker criterion and HTMT. We then tested the structural model through bootstrapping to assess the hypothesized paths. The results show that expected financial gains are driven primarily by behavioral intention, and are also supported directly by perceived value and trust. Behavioral intention rises mainly with trust and performance expectancy, while the effects of other adoption drivers are comparatively weaker. Service delivery quality contributes indirectly by strengthening perceived usefulness and trust, which subsequently improves intention and the expected dividend. The findings indicate that perceived financial benefits depend on a clear value pathway, credible institutional trust, and consistent service performance. The study therefore highlights practical priorities for cities: improve reliability and responsiveness, strengthen confidence through transparency and resolution mechanisms, and make the value-for-money case more legible to residents.

Urban Science doi: 10.3390/urbansci10050291

Authors: Gorana Mudronja Mladen Jardas Hrvoje Grofelnik

Ports are drivers of economic development, but at the same time, they create significant environmental pressures for port cities. Sustainable port development is an important aspect of urban and logistical planning in European coastal cities, helping to improve local air quality, the quality of life in port cities, and impact sustainable economic development. This research aims to analyze the relationship between investments in sustainable practices implemented in ports and air quality in port cities, based on a sample of five European ports observed from 2013 to 2024. The Fixed Effects (FE) estimation model was used as the estimation technique. The results indicate that higher investments in sustainable practices are associated with lower NO2 concentrations in port cities. This highlights the significance of sustainable investments in improving air quality in port cities while advancing urban sustainability and contributing to economic development. This paper contributes to understanding the role of ports as an important link in the urban energy transition and provides guidelines for further integration of environmental policies into port and city planning.

Urban Science doi: 10.3390/urbansci10050290

Authors: Eva Nedeliaková Kristína Ovary Bulková

Rail transport is the basis for the proper functioning of a transport system that is sustainable for future generations. It is safe and environmentally friendly; moreover, it is suitable for carrying a large number of passengers. Train connections should be operated following the requirements of the traveling public, as well as with the potential to reach those who have hitherto preferred individual car transport. The study aimed to identify the needs of current as well as potential rail users and to propose measures for improving service provision and supporting more sustainable transport possibilities. Given the ecological nature of rail transport and the high numbers of tourists using individual car transport in the summer and winter seasons, the study sought solutions to shift transport from road to rail infrastructure. Visitors to the area were approached directly during their visit as part of a transport–sociological survey conducted during periods of peak visitation, specifically in the summer and winter seasons. Drawing on findings from previous studies and the results of the transport–sociological survey, four universal variants were developed. The study applies to the method of practical permeability indicators. It evaluates variants of measures involving timetable adjustments, line modifications, and construction of new stations. It assesses their impact on reducing travel times and proper timetable management. The result of the study is to propose building a station on the railway infrastructure, which brings fundamental changes in increasing the practical capacity of the line and meets the goal of sustainability concerning increasing the number of connections and thus increasing the number of public service opportunities. The study addresses the growing pressure of individual car transport in a protected natural area and the need to shift demand towards more sustainable rail transport.

Urban Science doi: 10.3390/urbansci10050289

Authors: Sebastien Comin Denise Corsini Irene Vigevani Caterina Villa Christian Bettosini Elena Crescini Paolo Viskanic Francesco Ferrini Alessio Fini

The aim of this research was to quantify the capacity of different shrub species to remove atmospheric CO2, to adsorb particulate matter and to dissipate latent heat through transpiration. A total of 308 established plants comprising Deutzia scabra, Elaeagnus × ebbingei, Euonymus japonicus, Forsythia × intermedia, Laurus nobilis, Ligustrum vulgare, Pittosporum tobira, Prunus laurocerasus and Viburnum tinus were selected in Lugano (Switzerland) and Bolzano (Italy). Stem diameter, crown radius, Leaf Area Index, net CO2 assimilation per unit leaf area (Aleaf), transpiration, and stomatal conductance (gs) were measured during spring, summer, and fall. The net CO2 assimilation per unit of crown projection area and per plant were calculated by upscaling Aleaf using a multilayer model. Latent heat dissipation was calculated using the Penman–Monteith equation. The amount of PM trapped on leaves was measured using a gravimetric method. Differences in leaf area and leaf gas exchange among species affected their capacity to deliver specific ecosystem services. Forsythia, Pittosporum, Elaeagnus and Deutzia removed about 40% more CO2 per unit crown projection area than Laurus, Ligustrum, and Euonymus. Latent heat dissipation by shrubs was, on average, 130 W m−2, which is comparable to that of tree species. PM removal per unit leaf area was higher in species with sparse canopies and rough leaf surfaces.

Urban Science doi: 10.3390/urbansci10050288

Authors: Ledile Francina Malebana Maasago Mercy Sepadi Matlou Ingrid Mokgobu

Environmental health services play a critical role in communicable disease outbreaks by addressing environmental determinants of disease transmission. However, the scope, impact, and challenges of Environmental Health Practitioner (EHP)-led interventions remain insufficiently documented. Aim and objectives: This systematic review objectively assessed the role, impacts, and challenges of municipal environmental health services in outbreak response, with a focus on South Africa, to inform the standardisation and strengthening of disease surveillance and prevention. Methods: The PICO framework guided the development of search terms and research questions. PubMed, Scopus, Google Scholar, and Web of Science were searched for English-language, full-text studies published between 2010 and 2024. Studies not meeting these inclusion criteria were excluded. Screening and reporting followed PRISMA guidelines, and data were synthesised using a standardised extraction tool. Results: A total of 58 studies were included. The key EHP functions identified were water quality monitoring, vector control, food safety, waste management, and outbreak response. While South Africa demonstrated comparatively advanced systems, persistent implementation challenges remain, including the integration of environmental monitoring with disease surveillance. The findings emphasised the need for integrating environmental monitoring with disease surveillance systems and integrating WASH and climate-responsive strategies. Conclusions and recommendation: The review recommends strengthening guidelines and advancing evidence-based practice. Enhancing EHP roles within surveillance frameworks is essential for improving outbreak preparedness and public health resilience.

Urban Science doi: 10.3390/urbansci10050287

Authors: Hyun Kim Branislav Dimitrijevic

Extensive research has been conducted to develop technologies that enable paratransit systems to operate autonomously, including advanced sensing technologies and associated software. However, there remains a gap in research addressing adaptive operational algorithms for such systems under stochastic and dynamically evolving demand. To address this gap, this study develops an imitation-learning-assisted deep reinforcement learning (DRL) approach for autonomous shuttle routing. The proposed framework integrates generative adversarial imitation learning with proximal policy optimization to enable sequential pickup and drop-off decision-making under stochastic passenger demand without centralized re-optimization. The DRL agent was trained over approximately 1.5 million training steps and evaluated across 1000 episodes with stochastic passenger generation. Its performance was benchmarked against a deterministic dial-a-ride problem (DARP) solver implemented using Google’s OR-Tools, as well as online heuristic baselines. Results indicate that while heuristic methods achieve lower average time-based performance metrics, the proposed approach is capable of learning adaptive routing policies and demonstrates consistent behavior across diverse demand realizations. These findings highlight the feasibility of learning-based routing in controlled environments and provide a foundation for extending such approaches to more complex and realistic autonomous mobility systems.

Urban Science doi: 10.3390/urbansci10050286

Authors: Xuemei Zhu Hanwool Lee Sinan Zhong Samuel D. C. Towne Amaryllis H. Park Chanam Lee Wei Li Marcia G. Ory

The perception of livability varies by individual, sociocultural, and environmental factors. Little is known about environment-livability relationships in unique sociocultural contexts with predominantly Mexican-origin Hispanic populations. This study examines how neighborhood environments relate to residents’ perceived livability in selected neighborhoods in El Paso, Texas, and potential differences between Hispanic and non-Hispanic samples. We surveyed 2233 residents and generated GIS (ArcGIS 10.6.1) measures of their neighborhood environments. The binary livability outcome was derived from a survey question about satisfaction with their neighborhood as “a good place to live.” Three logistic regressions were estimated using the full sample and two subsamples (Hispanic and non-Hispanic). For the full sample, significant (p < 0.05) environmental predictors included social cohesion, crime safety, attractive surroundings, sidewalk availability and maintenance, surveillance and night lighting, walkable destinations, and land-use mix; significant interactions existed between Hispanic ethnicity and gender, between Hispanic ethnicity and the density of sit-down restaurants, as well as between age and crime safety. Comparing two subsample models, environmental features and personal health status were more influential in the Hispanic subsample, whereas personal and household factors were more influential in the non-Hispanic subsample. Culturally responsive designs should prioritize the most critical environmental improvements to effectively enhance livability.

Urban Science doi: 10.3390/urbansci10050285

Authors: Rasha Ali EL Ashmawy Amany A. Ragheb Ghada Ragheb Tasneem Amr Nourhane M. El-Haridi

This manuscript creates a framework for decision support based on green urbanism to direct the sustainable development of Gamasa, an Egyptian seaside city. The paper aims to convert the concepts of green urbanism into a multi-criteria evaluation that can support strategic urban development and prioritize spatial interventions. Sustainable mobility, green and blue infrastructure, energy and resource efficiency, urban form and density, social livability and public space quality, and governance and implementation feasibility are the six dimensions that are defined. These dimensions are derived from international sustainability literature and tailored to Gamasa’s particular challenges. The study’s methodology combines a multi-criteria decision-making approach based on the AHP with spatial analysis of land use, street hierarchy, building shape, and green space distribution. Weights for these dimensions are determined by expert-based pairwise comparisons, which are backed by a SWOT analysis. To prioritize priority zones for green transformation, the weighted framework is applied to four important urban areas: residential districts, a large urban park, the waterfront, and the main urban corridor. The top priorities, according to the results, are climate-responsive coastal design, increased green and blue infrastructure, and sustainable transportation. For quickly urbanizing coastal cities, the method demonstrates how the AHP operationalizes green urbanism into quantifiable, context-sensitive goals.

Urban Science doi: 10.3390/urbansci10050284

Authors: Silke Zöllner Uta Jüttner Andrew Angus

This paper examines how the growth and decline of agglomerations and peripheries in metropolitan regions can be understood in the context of Advanced Producer Service (APS) firm decisions, regional conditions and institutional policies. Focusing on Germany, it responds to divergent quantitative findings for Munich and Dresden and to outcome-oriented studies documenting spatial patterns, leaving underlying mechanisms under-specified. This study adopts an embedded qualitative case study design, analysing Munich and Dresden as contrasting metropolitan subunits within a shared national framework. Drawing on documentation, archival records and expert interviews with economic development and regional governance actors, it uses explanation building and template analysis to link empirical material to an analytical framework integrating firm, location and public authority perspectives. The results identify four recurrent configurations in the firm–location–policy nexus: reinforcing agglomeration, emerging limits to agglomeration, balancing peripheral growth and reinforced peripheral decline. These configurations show how the same metropolitan region can simultaneously exhibit core growth, constraints on further concentration, selective peripheral upgrading and cumulative peripheral disadvantage. Conceptually, this paper develops a mechanism-based account of APS-driven metropolitan development and proposes refined propositions that help reinterpret outcome-based studies on Munich and Dresden. More broadly, the configurations offer an analytical lens for analysing APS location dynamics and metropolitan governance challenges in other polycentric and federal contexts.

Urban Science doi: 10.3390/urbansci10050283

Authors: Erika Loučanová Miriam Olšiaková Florin Cornel Dumiter Marius Boiță

Although Smart City transitions are typically assessed using technological and financial indicators, the underlying structural correlates remain insufficiently explored. This study examines how different forms of capital within the Quintuple Helix model—natural, social, intellectual, economic and institutional (governance)—are associated with a country’s position in the Global Smart Cities Index and the Eco-Innovation Index. The methodology is based on data from 26 EU Member States. Correlation analysis was used to identify key factors of city performance, cluster analysis was applied to categorize countries/capitals based on their capital profiles and the impact of Smart Cities and eco-innovation. This study identifies three distinct clusters of EU countries/capitals, ranging from leaders to economies in transition. The results show that intellectual capital and institutional governance are the most significant correlates of Smart City success. In addition, governance emerged as a primary association of eco-innovation. These results provide a roadmap for lagging regions to optimize their Quintuple Helix synergies to achieve higher smart city rankings and environmental sustainability.

Urban Science doi: 10.3390/urbansci10050282

Authors: Van Quy Khuc Minh Anh Hoang Thi Thu Na Nguyen Thi Nguyet Nuong Nguyen Bich Ha Nguyen Ngoc Duc Doan

This study investigates the transition toward green transportation in Hanoi through a culture-centered perspective by integrating the Culture Tower (KAUC) framework with PLS-SEM analysis. Using survey data from 172 urban residents, the research examines how factors of knowledge, action, perceived utility, contribution, infrastructure, and social norms interact to shape green transport policy acceptance. The findings reveal that sustainable mobility functions as a layered cultural process rather than a simple behavioral sequence. Environmental awareness emerges as the central driver, exerting significant direct and indirect effects on contribution and policy acceptance, while green transportation infrastructure influences acceptance primarily through normative and cognitive pathways. The absence of strong experiential reinforcement between action, utility, and contribution suggests that behavioral engagement has not yet consolidated into stabilized cultural practice. By conceptualizing policy acceptance as the outcome of accumulated cultural layers rather than short-term cost–benefit evaluation, the study advances a systemic and culturally grounded approach to green transport governance. The results underscore the importance of reinforcing environmental knowledge, stabilizing social norms, ensuring reliable infrastructure, and fostering participatory contribution to achieve durable, green mobility transitions in rapidly urbanizing contexts.

Urban Science doi: 10.3390/urbansci10050281

Authors: Sanjay Kumar Kimihiro Sakagami

This review paper examines innovative urban design strategies for sustainable noise management through a structured analysis framed by ten guiding questions. It begins with an overview of conventional noise assessment technologies and progresses to advanced mitigation approaches. Core principles of sustainable urban design are explored, alongside evaluations of urban and transportation planning, traffic-reduction measures, green infrastructure, and resilient architectural strategies. Material innovations and modern noise-control technologies are presented as complementary solutions. Community-based methods, including citizen science and participatory planning, are highlighted for fostering inclusive governance. The discussion concludes by addressing key challenges and future directions, underscoring interdisciplinary collaboration to transform urban noise pollution into opportunities for healthier, more livable cities.

Urban Science doi: 10.3390/urbansci10050280

Authors: Nicole Chávez-García Joceline Salinas-Carrión Andrés Navas-Perrone Mario González-Rodríguez

Traffic accidents pose a persistent challenge for urban mobility, public safety, and sustainable development in smart cities, particularly in rapidly growing urban environments. This study presents a data-driven spatiotemporal analysis of traffic accidents in Ecuador, aimed at supporting evidence-based urban traffic management and road safety planning. Using large-scale historical accident records, the proposed approach combines spatial clustering and temporal forecasting techniques to characterize accident concentration patterns and temporal dynamics at national and metropolitan scales. Spatial accident hotspots are identified using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), enabling the detection of high-risk zones without imposing assumptions on cluster shape or size. This analysis reveals strong spatial concentration of accidents, with a limited number of clusters accounting for a substantial proportion of fatalities and injuries. Complementary temporal analysis is conducted using a multi-model ensemble framework to examine accident trends and seasonal patterns. This approach integrates SARIMA for linear stochastic modeling and Prophet for additive trend analysis, alongside two Long Short-Term Memory (LSTM) architectures: a direct 12-month vector output and a recursive horizon-3 model. By synthesizing these statistical and neural network-based methods through inverse-RMSE weighting, the study captures both stable seasonal cycles and non-linear, short-to-medium-term variations in accident frequency. Results show that traffic accidents in Ecuador exhibit stable diurnal and seasonal structures, alongside pronounced spatial heterogeneity across urban regions. The combined spatial and temporal insights provide a coherent representation of accident risk patterns, facilitating the prioritization of critical zones and high-risk periods. The resulting hotspot maps and multi-model forecasting horizons offer actionable information for smart city stakeholders, supporting targeted infrastructure interventions, adaptive enforcement strategies, and data-informed urban mobility policies. This work contributes to the broader understanding of traffic safety analytics as a core component of smart city decision-support systems.

Urban Science doi: 10.3390/urbansci10050279

Authors: Melissa Rovner Emily Talen

The National Register of Historic Places (NR) is a structured artifact of meaning-making that encodes disciplinary values linking architectural and cultural significance to wealth and stylistic distinction. In doing so, it systematically underrepresents vernacular, working-class, and the built environments of racially and ethnically marginalized communities. This paper uses artificial intelligence (AI) to examine how that meaning is constructed. We analyze the preservation record across three scales: a national dataset of 100,117 NR listings (1966–2025), a state-level profile of Illinois’s 1997 NR listings, and a close analysis of Lake Forest, Illinois, a community whose exceptional concentration of NR-listed estate architecture makes it an ideal site for examining how preservation significance has been defined and what it excludes. Two parallel AI methods are applied to eighteen Lake Forest nomination documents and their associated photographs. Natural Language Processing (NLP) analyzes nomination text to trace how preservation professionals connect buildings to cultural value; blind AI image analysis examines the same properties to assess how a model trained on cultural imagery constructs visual meaning independently. NLP analysis reveals a corpus dominated by architectural description, with social history, landscape, and labor systematically underrepresented. The visual analysis confirms and amplifies the nomination record’s class-based assumptions while reproducing the same omissions regarding labor, diversity, and community context. These findings inform debates about AI’s potential to audit existing listings and support nominations for underrepresented property types, while showing that without deliberate corrective design and policy reform, such tools are as likely to replicate the preservation system’s inequities as to repair them.

Urban Science doi: 10.3390/urbansci10050278

Authors: Susana Maia Vitória Souza Carlos Afonso Teixeira

This study proposes and tests an analytical framework for interpreting digitally monitored municipal biowaste collection services through comparable diagnostics of operational performance, additional effort, and emissions intensity. The framework was applied to 572 collection services recorded between July and December 2025 in the Municipality of Barreiro, Portugal, covering seven circuits operating under different urban morphologies and collection configurations. Service-level operational records were transformed into physically interpretable performance indicators and an additional operational effort index was derived from robust normalization of serviced container density and service time per kilometer. The results showed marked heterogeneity across service regimes, with the highest effort observed in residential circuits characterized by greater spatial and temporal demand, while the non-domestic and communal circuits remained at or below municipal reference conditions. At the municipal scale, operational effort was moderately associated with mass collected per kilometer (ρ = 0.490, n = 572), weakly and non-significantly associated with mass per hour (ρ = 0.075, p = 0.074), and negatively associated with mass per container (ρ = −0.325). For services operating above municipal reference conditions (Eesf > 0, n = 286), emissions intensity was negatively associated with both effort components and with the aggregate effort index, with the strongest association observed for Eesf (ρ = −0.554). The results indicate that higher operational effort tends to coincide with greater spatial mass recovery, but not with higher container-level yield or proportionate improvements in emissions performance. More broadly, the study shows that the analytical value of digital monitoring depends not only on data availability, but also on the ability to convert routine service records into interpretable diagnostics for municipal decision-making.

Urban Science doi: 10.3390/urbansci10050277

Authors: Fabio Capra-Ribeiro Jessica Peres Filippo Vegezzi Daniel Belandria

Implementation remains a central challenge in urban policy, yet the knowledge formats designed to bridge the gap between policy goals and on-the-ground delivery remain under-examined. This study treats 250 UN-Habitat Best Practice reports not as proof of effectiveness but as a standardized genre through which local interventions are narrated, compressed, and made portable for replication. We extract three focal sections, namely Results, Lessons Learned, and Transferability, apply systematic thematic coding with 906 open codes consolidated into axial categories, and compute co-occurrence networks using Jaccard similarity and Lift to detect thematic bundles, holes, and silos within and across sections. Three findings emerge. First, the reporting repertoire narrows progressively, as mean thematic richness declines by 28.2% from Results to Transfers while concentration increases 4.2 times, with substantive dimensions such as governance, equity, sustainability, and evidence losing prevalence to circulation-oriented themes. Second, formal bundle detection yields zero qualifying pairs across all six matrices, indicating a loosely coupled reporting grammar anchored by generic silos rather than integrated implementation packages. Third, structural holes concentrate at the pipeline’s end, where infrastructure transfer and sustainability as transferable value are the most systematically disconnected themes. These patterns reveal a portability paradox in which the reporting format achieves institutional legibility, making practices comparable within a shared vocabulary, but progressively filters out the physical, evidentiary, and context-sensitive content that operational reproduction would require.

Urban Science doi: 10.3390/urbansci10050276

Authors: Sara Qwaider Mohammad Sharif Zami Baqer M. Al-Ramadan Mohammad A. Hassanain Amer Al-Kharoubi

Urban community parks are important public open spaces (POSs) that support residents’ quality of life (QoL) by aiding recreation, social interaction, and physical activity. However, evidence on how to design and assess sustainable POS in Saudi Arabia remains limited, particularly in relation to the country’s hot–arid climate, socio-cultural context, and emerging urban development priorities. This study aims to develop a context-sensitive framework for the design and assessment of sustainable POSs (a scope of urban community parks) in Saudi Arabia using a mixed-methods approach. The study combined: (i) a structured review of the literature on POSs’ sustainability and QoL/subjective well-being (SWB); (ii) naturalistic field observations in two community parks in Al-Khobar (Shells Park and Prince Ibn-Jalawy Park); (iii) an on-site questionnaire survey of park users assessing satisfaction and self-reported well-being (n = 89); and (iv) structured expert interviews to refine and prioritize the framework elements (n = 15). The quantitative analysis included descriptive statistics, Pearson correlation analysis, and reliability testing using Cronbach’s alpha, the Mann–Whitney U test, and the Kruskal–Wallis test to explore the associations between perceived park attributes, user satisfaction, and self-reported well-being. The framework was iteratively refined through triangulation via the literature, field evidence, user feedback, and expert judgement, while expert responses were synthesized using weighted mean scores, simple ranking system, and the Relative Importance Index (RII). The findings indicate that shading and thermal comfort, safety, accessibility, maintenance, and cultural alignment are the most important design priorities in the Saudi Arabian context. The empirical assessment also highlights recurrent shortcomings in the selected parks, particularly inadequate heat mitigation measures, inconsistent maintenance, limited recreational infrastructure, and the weak integration of smart support features. Based on this triangulated evidence, the study proposes a framework comprising nine categories, 43 sub-categories, with 137 indicators organized across environmental, socio-cultural, economic, and smart-enabler considerations. The framework provides a practical and context-sensitive tool for evaluating existing parks, prioritizing interventions, and guiding future community park development in support the Quality-of-Life Programme of Saudi Vision 2030.

Urban Science doi: 10.3390/urbansci10050275

Authors: Reyhaneh Ahmadi Kaveh Ghamisi

Smart city governance increasingly relies on AI-enabled planning systems, digital twins, vulnerability scoring tools, and capital investment platforms to allocate climate-resilient housing and infrastructure investments. Yet existing smart-urbanism and adaptation frameworks do not adequately specify how such systems should encode well-being, equity, and climate uncertainty when translating urban data into ranked projects and funded portfolios. This paper develops the Caring Urban Governance Framework for AI-enabled urban prioritization through a structured scoping review and conceptual framework analysis integrating climate-risk decision-making under deep uncertainty, built-environment pathways affecting psychosocial well-being, and public-sector algorithmic accountability. The framework proposes a five-layer architecture linking urban form and infrastructure, climate exposure and environmental resources, psychosocial mediators of well-being, algorithmic design choices, and institutional governance, with explicit feedback loops. Its main outputs are an auditable decision architecture, eight mechanism-based propositions for empirical testing, an operational specification matrix for objective functions, equity constraints, robust logic, and documentation, and an analytical validation of construct clarity, coherence, literature congruence, and operationalizability. The analysis argues that aligning AI-enabled urban prioritization with SDG 11 requires treating well-being-supportive living conditions as a decision objective, constraining optimization with equity conditions, and institutionalizing auditability and contestability to reduce distributive and psychosocial harm in public investment planning.

Urban Science doi: 10.3390/urbansci10050274

Authors: Hsiao-I Kuo Jui-Ying Hung

As global urban centers transition into “Super-Aged Societies,” the paradigm of urban sustainability has shifted from mere housing provision to the development of Sustainable Care Retirement Communities (SCRCs). This study addresses a critical gap in the urban aging literature: the lack of culturally sensitive frameworks for social resilience in non-Western contexts. By integrating Hofstede’s Cultural Dimensions Theory, this research investigates how national culture influences the prioritization of community attributes within the “15 min city” framework. Methodologically, a hierarchical evaluation framework comprising 4 dimensions and 26 indicators was established. It employed the Fuzzy Delphi Method (FDM) to achieve expert consensus among stakeholders in Taiwan’s Long-term Care 3.0 ecosystem. Analysis using Double Triangular Fuzzy Numbers identified the “Charging Model,” “Staff-to-Resident Ratio,” and “Zoning with Care Continuity” as the highest-priority factors (Gi ≥ 7.8). These results indicate that in cultures with high uncertainty avoidance, institutional financial stability and human-centric staffing are perceived as the structural bedrock of social resilience. Furthermore, the study highlights the emergence of AI-driven “Active Sensing” environments as a pivotal component of technical resilience, mitigating the loneliness epidemic while maintaining institutional efficiency. The findings suggest that social resilience in SCRCs is not merely a product of physical accessibility but is theoretically inferred by experts to be deeply rooted in the synergy of Bonding and Bridging Social Capital, rather than being a directly measured outcome. This research provides urban planners and policy-makers with a robust, evidence-based toolkit to design inclusive, resilient, and culturally aligned aging-in-place environments in the face of unprecedented demographic challenges.

Urban Science doi: 10.3390/urbansci10050273

Authors: Efrén Hernández-Alvarez Bayron Alexander Ruiz-Blandon Mario Alberto Hernández-Tovar Rosario Marilu Bernaola-Paucar Gary Francis Rojas-Hurtado Veronica Zevallos-Guadalupe Alex Marcos Zevallos-Guadalupe Luis Armando Nieto Ramos Carlos Emérico Nieto Ramos

Urban green spaces play a key role in supporting biodiversity, climate regulation, and carbon storage in rapidly expanding cities. Urban and peri-urban parks can differ markedly in tree-community structure, floristic diversity, and carbon-storage capacity. The aim of the study was to compare these attributes between an urban and a peri-urban park. The study compared these attributes between an urban park and a peri-urban park in western Mexico using data collected in 500 m2 circular plots. Tree structure was assessed through diameter at breast height, height, crown diameter, basal area, and crown projection area, while floristic composition and diversity were evaluated using richness, Shannon, Simpson, Pielou, and Menhinick indices. Aboveground biomass, belowground biomass, and carbon stocks were estimated using generalized allometric equations. A total of 1675 trees belonging to 19 families, 33 genera, and 49 species were recorded. The peri-urban park showed greater structural development, with significantly higher DBH, height, crown diameter, basal area, biomass, and carbon stocks, whereas the urban park supported greater species richness and higher Shannon diversity. Species composition also differed strongly between parks, and carbon storage was concentrated in a reduced number of dominant taxa in each site. DBH was the structural variable most strongly associated with total carbon per tree. These findings show that floristic diversity and carbon-storage capacity do not necessarily increase in parallel and that urban and peri-urban parks can provide contrasting but complementary ecological functions.

Urban Science doi: 10.3390/urbansci10050272

Authors: Bárbara Polo-Martín

StoryMapping has emerged as an accessible geotechnological approach that combines spatial analysis, interactive cartography and digital storytelling to communicate urban landscape transformations. This study aims to demonstrate the methodological potential of StoryMaps for integrating historical cartography, GIS-based analysis and narrative visualisation to explain long-term urban landscape change in an accessible and scientifically rigorous way. Using a case study of Madrid, the research integrates more than 150 years of historical maps, georeferenced images and thematic GIS layers to visualise shifts in blue–green infrastructures, land-use patterns and morphological configurations. The methodology includes the compilation of historical cartographic sources, GIS processing of contemporary datasets, georeferencing of archival materials and the construction of an interactive narrative using ArcGIS Pro 3.6 StoryMaps. Results show that StoryMapping enhances public understanding of complex urban processes, supports participatory planning, and provides a bridge between technical analyses and community engagement. The study concludes that StoryMapping is not only a powerful communication tool but also a valuable geotechnological solution for sustainable landscape planning, complementing traditional GIS approaches and promoting interdisciplinary perspectives in urban studies.

Urban Science doi: 10.3390/urbansci10050271

Authors: Farah Gasmi Mohamed H. Aly

Due to climate change and its increased variability, as well as the extreme weather events, flooding is becoming a major natural threat causing profound economic, social, and ecological impact. This paper systematically reviews 89 peer-reviewed articles published between 2010 and 2024 on flood risk assessment approaches, including geospatial techniques and methods for flooding, using the PRISMA framework and the ScienceDirect and Web of Science databases. GIS and remote sensing are the most popular tools for flood hazard mapping, and hydrodynamic models such as HEC-RAS and MIKE FLOOD dominate flood simulation. Machine learning algorithms, multi-criteria decision analysis (MCDA), and climate scenario analysis have also emerged as increasingly prominent methodological contributions to flood risk frameworks. This review makes a novel contribution by providing the first systematic synthesis of geospatial flood risk assessment methods, explicitly quantifying both the urban–rural research imbalance and the degree of hazard, vulnerability, and exposure integration across the literature. Specifically, only 13 (2.7%) of all eligible articles addressed rural flooding, despite the profound socioeconomic impacts that disproportionately affect these communities, and only 16% of included studies integrated any combination of hazard, vulnerability, and exposure components within current assessment approaches. This review highlights the importance of interdisciplinary collaboration and sensitivity to rural contexts in cultivating resilience and fostering equitable flood risk management.

Urban Science doi: 10.3390/urbansci10050270

Authors: Steven Keener Tucker Keener Braedon Taylor

Automatic license plate reader (ALPR) cameras and gunshot detection system (GDS) technology represent rapidly expanding forms of surveillance. Despite their prevalence, empirical literature regarding these tools remains limited, particularly concerning their geographic distribution across the United States. This study addresses this gap by conducting a geospatial analysis of crowdsourced ALPR and GDS locations throughout Virginia. Utilizing Geographic Information Systems (GIS), we mapped the concentrations of this technology and analyzed the racial demographic profiles of the most heavily surveilled communities. Our results identify distinct clusters of surveillance technology hubs across Virginia. In these high-intensity areas, surveillance technology is frequently concentrated in and around communities of color. These findings carry an array of implications, including the risk that over-surveilled neighborhoods may disproportionately suffer from the abuse or misuse of these tools. Furthermore, this distribution reflects a historical legacy within the criminal justice system of disproportionately monitoring marginalized populations. The limitations of this analysis are equally revealing: the reliance on crowdsourced data due to a lack of verifiable, publicly accessible coordinates underscores an ongoing lack of transparency.

Urban Science doi: 10.3390/urbansci10050269

Authors: Lankyung Kim Chul Jeong Min-Hui Chang

This study applies the Actor-Centered Power (ACP) framework to analyze urban green-space governance in three Asian cities, focusing on how power is distributed and exercised among actors in the management of their representative multipurpose parks: Seoul Forest in Seoul, Da’an Forest Park in Taipei, and Yoyogi Park in Tokyo. Conventionally used in large-scale forest governance in the Global South, ACP is extended here to East Asian cities of the Global North. This can provide nascent insight into how coercion, (dis)incentives, and information operate across different institutions. The study found that the initial formation of the parks was driven by potent actors through coercive measures in all three cities. While Seoul maintains centralized statutory governance under the national act, Taipei adopts a decentralized governance model that foregrounds subordinate actors, notably exemplified by the higher education-oriented foundation. This organization promotes citizen science involvement and community-based stewardship. Tokyo, by contrast, uses a public–private partnership model that supports private sector commercial collaboration. This comparative case study demonstrates that the ACP framework is well-suited for analyzing urban green-space governance, as it distinguishes between power subjects (potentates and subordinates) and power sources (coercion, incentives, and information), providing theoretical and managerial implications. Through the lens of the ACP framework, this study argues that distinct institutional arrangements produce divergent power configurations for urban green-space management even within similarly developed urban contexts.

Urban Science doi: 10.3390/urbansci10050268

Authors: Manuel Antonio Abarca Zaquinaula David Santiago Carrera Molina María Gabriela Suasnavas Rodriguez Melissa Paulina Calle Íñiguez Diana Karina Vinueza Morales Micaela Abygail Segura Flores

Urban destinations increasingly incorporate green–blue infrastructure, sensory-balanced public spaces, and microclimate-responsive design to mitigate visitor fatigue and support sustainable tourism experiences. To understand how insights from broader tourism environments, particularly nature-based contexts, can inform emerging urban well-being strategies, this study conducts a global bibliometric review (2005–2025) on psychological restoration, stress relief, and visitor well-being. Using Scopus and a Boolean search combining mental health constructs, tourism setting, and analytical approaches, 825 records were identified, and 149 articles were retained after applying eligibility criteria. Science mapping and performance analyses reveal accelerated post-2018 growth and three dominant knowledge clusters centered on restoration pathways, environmental determinants, and behavioral/hospitality components. Based on these patterns, this study introduces the RESTOR-URBAN model, integrating environmental moderators, psychological mechanisms, and behavioral interactions that jointly shape stress reduction and emotional well-being across urban tourism systems. The results show increasing relevance of micro-restorative experiences, thermal comfort management, and stress-aware service design, while highlighting persistent methodological heterogeneity and limited integration of environmental co-data (Universal Thermal Climate Index (UTCI), Physiological Equivalent Temperature (PET), and Discomfort Index (DI)). The findings suggest that restoration-based evidence from nature-based tourism can inform sustainable urban tourism planning, hospitality practice, and visitor experience design, and propose a research agenda emphasizing standardized well-being indicators, longitudinal and structural equation modeling (SEM)-based approaches, and environmental quality variables for resilient, health-oriented urban destinations.

Urban Science doi: 10.3390/urbansci10050267

Authors: Andrzej Szymon Borkowski Filip Pawlikowski Anna Ptaszek Patrycja Raczkowska Wiktoria Winiarska Natalia Wyrzykowska

The development of Building Information Modeling (BIM) and Generative Design (GD) methods supported by artificial intelligence opens up new possibilities in the field of urban planning analyses and the verification of land-use compliance with local regulations. The aim of this study was to assess the potential of the Autodesk Forma Site Design environment, which utilizes BIM technology and generative methods, in streamlining planning processes, using the example of an analysis of the compliance of existing development with local regulations. The research was conducted based on a case study of selected plots located in the Polish city of Włocławek, covered by the 2004 Local Spatial Development Plan (LDSP). The scope of work included the analysis of planning documents, parametric modeling in Autodesk Forma Site Design, and the generation of development variants using the Archistar and One Click LCA Generative Design plugins. The results indicate that Generative Design tools can effectively support the early stages of urban planning analyses, enabling the rapid generation and comparison of land-use variants as well as a preliminary assessment of their compliance with planning regulations. At the same time, significant technological limitations were identified, including the lack of full determinism of parameters, difficulties in the automatic interpretation of complex planning regulations, and the need for manual correction of results. Consequently, the current level of development of generative tools allows for a partial streamlining of planning processes, but does not yet provide a basis for the full automation of verifying the compliance of land-use plans with local regulations.

Urban Science doi: 10.3390/urbansci10050266

Authors: Jing Jiang Manfredo Manfredini

Rapid urbanisation in contemporary China has intensified pressures on private living environments, prompting domestic practices to increasingly unfold within third places, specifically privately owned commercial interiors. A representative example is the Starbucks coffeehouse, which explicitly positions itself as a “third place” through its “home away from home” model. This study examines how activities traditionally associated with the private home are enacted within the interiors of Starbucks China. Adopting a qualitative single-case design with two embedded subcases, a campus store and a community store, this research draws on ethnographic observations and interviews. Guided by Baudrillard’s hyperreality and Deleuze and Guattari’s assemblage framework, it analyses the deployment and reception of commercial assemblages with spatial configurations, interaction routines, and expressive means that are conceived as substitutes for the social and emotional functions of the home. Findings show that Starbucks’ standardised design and service elements establish homelike conditions that effectively dissipate the intrinsic public/private contradiction of these spaces; yet they concurrently foster relevant everyday counter-practices that transcend such contradictions. These contestational practices offer compensatory comfort, caregiving, and social encounter for those lacking adequate private space. The study argues that such third places reveal critical shifts in the use of public space, offering insights into the changing nature, lived experience, and governance implications of public space in contemporary cities.

Urban Science doi: 10.3390/urbansci10050265

Authors: Iuria Betco Cláudia M. Viana Eduardo Gomes Jorge Rocha Diogo Gaspar Silva

This paper offers a comprehensive overview of academic research on sentiment analysis in urban built environments from 2000 to 2025. Based on data from the scientific database Scopus and drawing on bibliometric tools like Bibliometrix (R) and VOSviewer for performance analysis and scientific mapping, it identifies publication trends, key influential works, leading authors and institutions, funding sources, and thematic clusters. The final dataset comprises 1315 English-language documents authored by 3855 researchers across 160 sources, with a total of 14,058 citations worldwide. The academic production increased after 2009, peaking in 2025. Keyword and network analyses highlight central themes (and methodological approaches) to the study of sentiment analysis in urban built environments. These include social media platforms like Twitter/X, machine learning, smart cities, artificial intelligence, mental health, and urban planning. China, the USA, and India lead in publication output. Over the last twenty-five years, key publication outlets included Sustainability (Switzerland), Cities, and the International Journal of Environmental Research and Public Health, while the National Natural Science Foundation of China has been the main funder. The paper discusses how sentiment analysis can support urban planning and public health by linking environmental features to well-being and explores emerging methodological trends like deep learning, multimodal approaches, and context-aware models. Overall, it maps the field’s intellectual landscape and argues in future directions for human-centered, data-driven urban decision-making.

Urban Science doi: 10.3390/urbansci10050264

Authors: Diego Gómez-Carmona Ismael Traba Outes Serafín Cruces-Montes Pedro Pablo Marín Dueñas José Miguel Mota Macías

Urban tourism destinations increasingly rely on specialized segments such as wine tourism. However, limited research examines how electronic word-of-mouth (e-WOM) and personal recommendations jointly influence destination loyalty through experiential and relational pathways in urban settings. This study develops and tests an integrative model linking e-WOM to destination loyalty through experience, trust, and satisfaction as mediating mechanisms, grounded in social exchange theory and expectancy-disconfirmation theory. Data were collected from 326 tourists visiting Jerez de la Frontera (Spain) via intercept surveys at transportation terminals and analyzed using structural equation modelling with maximum likelihood estimation and bootstrapping. All nine hypothesized relationships were positive and significant, collectively accounting for 89.3% of the variance in destination loyalty. Satisfaction emerged as the strongest predictor of loyalty, far exceeding the direct effects of experience and trust, while e-WOM exerted the strongest influence on experience. Indirect effects confirmed that e-WOM influences loyalty through experience and trust pathways. This research provides the first model integrating pre-visit communication influences with experiential and relational constructs to explain destination loyalty in an urban context. Findings indicate that urban destinations should prioritize visitor satisfaction as the primary loyalty driver, while strategically managing digital reputation and ensuring alignment between online recommendations and actual destination experiences.

Urban Science doi: 10.3390/urbansci10050263

Authors: José Andrés Bravo Jiménez Rosa Armijos-González Fausto López-Rodríguez

Yacuri National Park (YNP) is a Ramsar site located within Ecuador’s Podocarpus-El Cóndor Biosphere Reserve. The Park faces critical threats from illegal mining, livestock grazing, wildfires and the harvesting of wax palms. This study employed participatory action research to co-design a Communication, Education and Public Engagement (CEPA) plan with park managers and local communities as equal partners. Moving beyond traditional, top-down information campaigns, the CEPA framework establishes a co-governance model that integrates indigenous knowledge with local socio-economic realities. The plan implements four targeted interventions: (1) strengthening community fire brigades (BRICOM); (2) promoting culturally appropriate alternatives to Holy Week wax palm harvesting; (3) establishing participatory waste management; and (4) engaging tourists as conservation allies through experiential learning. Strategic alliances with municipalities, universities, and civil society organizations provide institutional backing and secure resources, while a participatory monitoring system using SMART indicators tracks behavioral and ecological outcomes. Ultimately, the findings demonstrate that conserving culturally complex, biodiverse landscapes requires social legitimacy, environmental justice and equitable power-sharing. Recognizing local communities as co-managers is essential to ensuring the long-term protection of Andean ecosystems.

Urban Science doi: 10.3390/urbansci10050262

Authors: Sanjay Kay Sagar Sabrina Sorlini Satesh Kumar Devrajani Athanasia K. Tolkou

Coagulation-based technologies are increasingly recognized as key for controlling fluoride and hexavalent chromium in urban water and wastewater. Combined geogenic and industrial sources often drive chronic exposure and create an underrecognized public health burden. This review synthesizes current knowledge on the occurrence, speciation, and toxicology of F− and Cr(VI) in urban systems, links regulatory targets to health outcomes, and critically examines conventional, advanced, and electrochemical coagulation processes for their removal under realistic water-quality conditions. Mechanistic sections describe how aluminum-, iron-, magnesium- and zirconium-based coagulants, including pre-polymerized and composite formulations (e.g., IPC-type coagulants, PSiFAC-Mg, ZrCl4), remove fluoride via Al–F complexation, Al–F–OH co-precipitation, ion exchange, and sweep flocculation, while Cr(VI) control relies on Fe(II)-mediated reduction to Cr(III), followed by adsorption and co-precipitation with metal hydroxides. The review assesses how water chemistry and operating conditions affect single- and multi-contaminant removal, highlighting competition among fluoride, Cr(VI), nutrients, and other oxyanions. Performance data from bench-, pilot-, and selected full-scale studies show that optimized coagulation and electrocoagulation can substantially reduce fluoride and Cr(VI) (to drinking-water-relevant levels) in diverse urban waters, but also reveal persistent issues of sludge generation and stability, residual metals, process robustness, and cost. The review identifies priorities, including long-term urban-scale assessments, low-toxicity green coagulants, life-cycle and health impact assessments, and real-time coagulation control for fluoride and Cr(VI).

Urban Science doi: 10.3390/urbansci10050261

Authors: Joana Matos Carla I. Martins Ricardo Simoes

The transition to a circular economy (CE) is a critical challenge for the urban built environment, particularly within the Building and Construction sector. This study explores the application of circularity micro-indicators to assess the use of plastic materials in two Portuguese construction approaches: traditional (CS1) and modular (CS2). A set of four relevant micro-indicators—Material Circularity Indicator (MCI), Recycled Content Performance Indicator (RPI), Circular Design Guidelines (CDG), and Circular Economy Implementation Potential (CEIP)—was selected to evaluate material circularity at the product and system levels. The novelty of this study lies in selecting and applying the most relevant circularity indicators from the literature to plastic products in construction, providing the first practical demonstration of their use and offering actionable tools to support stakeholders in material selection, design decisions, and circularity assessment. Findings show that modular construction demonstrates a stronger alignment with CE principles compared to traditional methods, although both cases present low overall levels of circularity. For instance, the Material Circularity Indicator (MCI) ranged from 8.4% in the traditional building (CS1) to 15.2% in the modular building (CS2), quantitatively illustrating the circularity potential of modular construction. Key strategic opportunities for improvement include design for disassembly, the elimination of toxic or scarce materials, improved recyclability of plastic components, and the integration of on-site material separation and recovery zones. Strengthening waste management systems is also essential to enhance the quality and reliability of recycled plastic materials. The study highlights the value of micro-indicators as practical tools to support evidence-based decision-making in material selection, design strategies, and circular construction planning. By guiding more sustainable practices in urban construction, these indicators can play a pivotal role in accelerating the sector’s transition toward a circular and resource-efficient economy. Methodologically, the study adopts a collaborative case-study approach with an industry partner, involving brainstorming sessions with experts in CE and circularity indicators to select representative buildings, and identify indicators from the literature based on data availability and relevance for construction plastic products, which are then applied to real project data, complemented by exploratory improvement scenarios.

Urban Science doi: 10.3390/urbansci10050260

Authors: Dixu Liu Zhongsheng Wang Yang Yang Chuanjie Zhao Wei Zhang Jie Dong

Urban underground space resource (UUSR) constitutes a critical natural resource and a vital component of the natural environment, whose rational utilization is essential for the sustainable development of cities. Mathematical models are indispensable for the multi-object evaluation of UUSR. However, in previous research based on traditional mathematical models, neither the continuous expression of evaluation results has been considered, nor has the comparability been addressed. In this paper, the interval continuous mathematical model (ICMM) is presented at the theoretical level for UUSR multi-object evaluation. By achieving the continuous distribution of quantitative values of evaluation indicators, removing the step-like output features of evaluation results, and eliminating predefined grade boundaries, the ICMM achieves continuous expression of the results and improves their comparability across different areas. The correlation analysis conducted on the UUSR evaluation indicators demonstrates a significant monotonic relationship between the indicator value and the evaluation result, regardless of the increasing trend or the decreasing trend. Finally, a numerical experiment clearly demonstrates that the ICMM is valid for evaluating different UUSR objects.

Urban Science doi: 10.3390/urbansci10050259

Authors: Chunfeng Yang Mengru Zhou Hanbin Wei Chunxiang Dong

In response to environmental degradation and social inequities exacerbated by automobile-dependent urban sprawl, this study proposes a framework for dynamic delineation and vitality assessment of 15-min walkable neighborhoods, using Baohe District, Hefei, China as a case study. Static service catchments were constructed using POI and road network data, then refined using one week’s mobile phone signaling trajectories calibrated to actual walking behavior, yielding 143 validated living circles (out of 156 initially delineated). These circles are classified into five typologies: commercial-residential, industrial-residential, educational-residential, predominantly residential, and public-service-oriented. A dual-index system—Facility Vitality Index (FVI) and Population Vitality Index (PVI)—is developed and synthesized into a Composite Vitality Index (VI) through normalization and weighting. Results show that only 27.3% of living circles achieve high vitality in both dimensions, indicating widespread service–demand misalignment. Conversely, 61.5% exhibit low or very low vitality, forming a “vitality depression” around the urban periphery—a pattern of service poverty with significant socioeconomic implications. High-vitality circles cluster along the Binhu New District corridor, while low-vitality circles concentrate in industrial parks (e.g., Feinan Industrial Park) and transport hubs (e.g., Hefei South Railway Station). The historic core lacks micro-infrastructures, whereas new districts—despite high-standard amenities—suffer from weak pedestrian activity. To address these deficiencies, we propose a differentiated zoning strategy: retrofitting micro-infrastructures in legacy neighborhoods, applying Transit-Oriented Development (TOD) principles in new urban extensions, and integrating community-serving functions within industrial peripheries. This framework provides actionable protocols for data-informed governance of 15-min living circles.

Urban Science doi: 10.3390/urbansci10050258

Authors: Joseph Appelbaum Assaf Peled

With the need for increasing energy demand due to population growth in cities, and advancements in the efficiency of semi-transparent photovoltaic (ST-PV) technology, the integration of ST-PV modules into building windows has become feasible. This manuscript presents a novel analytical methodology for estimating incident solar energy on vertical PV modules integrated into building facades in an urban environment, emphasizing shade caused by nearby buildings. Monthly and annual direct-beam, diffusion, and global energies are calculated for different wall heights, building separation, and orientation. In addition, the distribution of the incident energy along the height of the wall is evaluated, indicating a non-uniform distribution. The incident diffusion energy is compared between isotropic and anisotropic models. The anisotropic model predicts higher diffusion energy by 3.5% to 14.5%, depending on the building separation. The incident energy on building facades is calculated for locations at low-mid (32°6’ N) and at high-mid (52.2° N) latitudes. The results show, for example, that both the front side of a front-building wall and the front side of a rear-building wall receive the same amount of annual global energy—913 kWh/m2—for a separation of 25 m between the buildings. Decreasing the distance from 25 m to 10 m decreases the annual incident global energy on a rear-building wall by 15%.

Urban Science doi: 10.3390/urbansci10050257

Authors: Vahagn Muradyan Rima Avetisyan Shushanik Asmaryan Anahit Khlghatyan Azatuhi Hovsepyan Garegin Tepanosyan Andrea Bergamaschi Fabio Dell’Acqua

This paper investigates the prediction of urban air temperature (Tair) from satellite-derived land surface temperature (LST) in the complex urban and topographic environment of Yerevan, Armenia. Building on previous work that demonstrated the effectiveness of machine learning (ML) approaches for point-based Tair estimation using Partial Least-Squares Regression (PLSR) with multiple environmental variables, this study shifts the focus to the spatial distribution of Tair. Several prediction methods and input variable combinations are evaluated to generate gridded Tair maps, which are assessed for spatial consistency against expected patterns driven by land cover, elevation, local knowledge, and spot observations. In total, five predicting methods were used—one regression approach (PLSR) and four ML methods: random forest (RF), quantile regression forest (QRF), support vector machine (SVM), multilayer perception (MLP). RF and QRF deliver the best overall results, with RF achieving the highest testing R2 (0.74) and lowest RMSE (0.56). Spatial patterns are similar for PLSR, RF and QRF, highlighting cooler northern high-altitude areas and warmer southern urban areas. Overall, the results confirm the reliability of the proposed Tair spatial mapping methods in complex urban environments.

Urban Science doi: 10.3390/urbansci10050256

Authors: José Carlos Collado-González Pablo Juan Cárdenas-García

Although the literature has extensively analyzed the determinants of tourist expenditure, studies focusing on second home tourism are scarce. Moreover, they tend to treat this segment as a homogeneous group, without delving into the existence of differentiated consumption patterns within non-market tourism. In this context, this paper analyzes the case of Spain, using a database comprising 1,253,115 observations for the period 2015–2024. First, linear regression models with interaction terms are estimated, and non-parametric tests are applied to evaluate the differences in tourist expenditure between market and non-market tourists. Specifically, market tourists refer to those staying in paid accommodation whereas non-market tourists are those using accommodation without a direct economic transaction. The results show that non-market tourists present lower direct expenditure per stay; however, their longer stays and more balanced and repetitive temporal distribution contribute to sustaining the economic activity of the destinations. Second, a segmentation analysis using the k-means clustering algorithm is applied to identify differentiated spending patterns within non-market tourism, revealing significant heterogeneity in the expenditure patterns of second home tourism. These findings suggest the suitability of adopting more segmented tourism management strategies and promoting this type of tourism as a mechanism to reduce seasonality in specialized destinations.

Urban Science doi: 10.3390/urbansci10050255

Authors: Idoia Landa-Oregi Itsaso Gonzalez-Ochoantesana Maite Anaya-Rodríguez Bruce Wilson Marco Amati

Urban greening has transitioned from a supplementary component of urban development to a central element in contemporary planning policies, driven by its recognized environmental, social, and health benefits. This paper explores urban greening processes through the lens of Human-Centered Design (HCD), an approach that emphasizes iterative, participatory, and user-oriented approaches. While public participation in urban planning is traditionally framed through statutory procedures and deliberative models, HCD offers a distinct perspective by treating engagement as a design process aimed at deeply understanding and integrating citizen needs into the process. This study compares two internationally acclaimed cities, Melbourne, Australia, and Vitoria-Gasteiz, Spain, focusing on their urban greening strategies and citizen engagement mechanisms. Using HCD as an analytical framework, the research investigates how socio-political and cultural contexts shape participatory practices, the barriers planners face, and how these impact the effectiveness and sustainability of greening initiatives. The findings underscore the value of HCD in fostering long-term citizen relationships, adapting greening solutions to local contexts, and addressing the methodological gaps in participatory urban design. Ultimately, the paper advocates for a more structured, context-sensitive, and human-centered approach to citizen engagement.

Urban Science doi: 10.3390/urbansci10050254

Authors: Elena Bogan Alexandru-Ionuț Bănescu Florina Tatu Elena Grigore

For the environment and the daily life of urban settlements, in the context of contemporary challenges, severe meteorological events rank second worldwide. Therefore, these events tend to become a real threat to human society and to specific economic activities. The main objective of this study is to analyze the spatio-temporal evolution of severe meteorological events in urban environments and to assess their relationship with atmospheric circulation regimes and urban thermal conditions. The analysis focuses on five types of severe events (significant atmospheric precipitation, hail, strong winds, tornadic structures, and cloud-to-ground lightning) recorded in 11 cities located in the historical region of Muntenia, Romania, over the period 2014–2024. The methodological framework is based on three complementary components. First, a new database was developed by integrating information from multiple sources, including the National Meteorological Administration (ANM), the European Severe Storms Laboratory (ESSL), international databases, and validated media reports, with spatio-temporal filtering and aggregation into synoptic episodes. Second, atmospheric circulation regimes were identified using ECMWF ERA5 reanalysis data, based on geopotential height anomalies at the 500 hPa level, allowing the classification of large-scale synoptic patterns. Third, urban thermal conditions were assessed using the ECMWF CERRA regional reanalysis dataset, which provides high-resolution air temperature data, enabling the analysis of urban–peri-urban thermal contrasts and the estimation of the urban heat island effect. The results highlight a total of 997 severe meteorological events, of which 253 (25.6%) were recorded in the analyzed urban areas, 85 (15.9%) in other towns, and 583 (58.5%) in rural areas. The analysis reveals pronounced interannual and intraseasonal variability, as well as distinct spatial clustering patterns, particularly in urban and peri-urban zones. Among the circulation regimes, the Zonal Regime exhibits the highest event rate, suggesting increased favorability for severe weather occurrence, while other regimes show weaker or even inhibitory effects. In addition, most severe events were associated with positive urban–peri-urban temperature contrasts, indicating an active contribution of the urban heat island effect. By combining observational data, synoptic-scale analysis, and urban-scale thermal assessment, this study provides an integrated regional perspective on severe meteorological events and contributes to the enrichment of data sources in the region, while improving the understanding of their dynamics in urban environments affected by data limitations.

Urban Science doi: 10.3390/urbansci10050253

Authors: William Camilo Enciso-Díaz Carlos Alfonso Zafra-Mejía Amed Bonilla Pérez

Urban growth and climate change intensify urban heat islands (UHIs), altering atmospheric stability and promoting the accumulation of particulate matter ≤ 10 µm (PM10) and particulate matter ≤ 2.5 µm (PM2.5), particularly in high-altitude megacities. However, there remains a scarcity of integrated dynamic models capable of representing these interactions at the intra-urban scale. This study develops a socio-environmental dynamic model to evaluate the influence of UHIs on PM10 and PM2.5 concentrations across localities of a high-altitude Latin American megacity (Bogotá, Colombia). A dynamic simulation model was developed in Vensim®, integrating temperature, PM10, PM2.5, and citizen perception data. Statistical and spatial analyses were conducted to represent intra-urban thermo-atmospheric interactions. The results show that the model captures the influence of UHIs on PM10 and PM2.5 concentrations. Higher PM concentrations are simulated in localities with high imperviousness (PM10: 33.4–50.4 µg/m3; PM2.5: 21.5–25.1 µg/m3) and lower PM concentrations in areas with greater vegetation cover. Sensitivity analysis of the dynamic model reveals nonlinear amplifications of up to 15–20 µg/m3 in PM10 and 8–10 µg/m3 in PM2.5 associated with small thermal variations (1–2 °C). Under scenarios with significant UHI intensity, increases reach 4–6 µg/m3 in PM10 and 3–4 µg/m3 in PM2.5. These findings confirm that UHIs act as amplifiers of pollution and that urban thermal interventions could reduce PM concentrations by up to 10–20%.

Urban Science doi: 10.3390/urbansci10050252

Authors: Angélica Tirado-Lozada Diego Venegas-Vásconez

Assessing carbon footprints has become increasingly important globally as a key tool for quantifying environmental impacts and supporting sustainable decision-making. However, although allegorical floats—central elements of large-scale parades in internationally recognized cultural festivals such as the Rose Parade in Pasadena, USA (RPP), the Rio de Janeiro Carnival, Brazil (RJC), the Black and White Carnival in San Juan de Pasto, Colombia (BWC), and the Fruit and Flower Festival in Ambato, Ecuador (FFF)—represent significant expressions of cultural heritage and artistic creativity, their environmental impact has received limited attention in sustainability research. The primary objective was to quantify the carbon emissions associated with constructing these temporary structures. The methodology integrated geometric surface estimation with carbon accounting principles commonly applied in life-cycle assessment. Emissions were calculated based on the material composition of the structural, covering, and finishing stages, and normalized using two indicators: kilograms of CO2 equivalent (kg CO2e) per square meter of float surface area and kg CO2e per float. Results indicate that emission intensity varies substantially across festivals, with RJC exhibiting the highest value (approximately 9 kg CO2e/m2) due to extensive use of synthetic materials, while BWC demonstrates the lowest intensity (approximately 4.3 kg CO2e/m2) as a result of greater reliance on wood- and paper-based components. When assessed per float, the large scale of RJC structures leads to emissions exceeding 30,000 kg CO2e per float, whereas FFF floats generate less than 1000 kg CO2e due to their smaller dimensions and use of natural materials. This research constitutes the first comparative carbon assessment of allegorical float construction and advances the emerging intersection of cultural heritage studies and environmental sustainability.

Urban Science doi: 10.3390/urbansci10050251

Authors: Manel Mrabet Maha Sliti

Rapid urbanization in Saudi Arabia puts increasing pressure on energy, water, mobility, and waste-management systems, strengthening the need for evidence-based smart-city policy under Vision 2030. Rather than offering a descriptive inventory of projects, this paper develops a verification-oriented framework for assessing smart-city initiatives in the Kingdom. The framework is built on four principles: (i) distinguishing national contextual indicators from city-level evidence, (ii) separating stated ambitions from observed outcomes, (iii) applying an evidence-grading rubric that prioritizes publicly verifiable mechanisms and performance indicators over anecdotal or promotional claims, and (iv) introducing a readiness–impact matrix adapted to Saudi climatic, infrastructural, and institutional conditions. The framework is applied to major Saudi smart-city cases, including NEOM, KAEC, Riyadh, Jeddah, Makkah, and Madinah. The analysis shows that the strongest publicly documented evidence is concentrated in selected sectoral applications, particularly demand response and smart-building control in electricity systems, leak detection and pressure management in water networks, and intelligent traffic management in urban transport. These cases indicate plausible pathways for improving service efficiency and reducing resource waste; however, publicly verifiable city-level outcome data remain limited, fragmented, and uneven across cases. In response, the paper proposes a policy playbook centered on KPI transparency, interoperable data governance, cybersecurity safeguards, and public–private partnership templates to improve the measurability, comparability, and scalability of smart-city outcomes. By formalizing verification and cross-case assessment, the study contributes a reproducible methodological basis for evaluating smart-city progress and prioritizing future investments in Saudi Arabia.

Urban Science doi: 10.3390/urbansci10050250

Authors: Dame Dimitrovski Zoran Markov Simona Domazetovska Markovska Maja Anachkova Nikola Manev

Urban air pollution in Skopje, a city with complex topography, is strongly influenced by traffic emissions, household heating, industrial activities, and meteorological conditions, leading to pronounced spatial and seasonal variability. The objective of this study is to assess the contribution of major urban emission sources to air quality in Skopje, with a focus on traffic pollution, and to quantify their seasonal influence on NO2, PM10, and PM2.5 concentrations using a high-resolution urban dispersion modelling approach. The methodology is based on the ADMS-Urban dispersion modelling system, integrating traffic activity data as line sources, together with area sources representing household heating, point sources representing industrial facilities, and seasonally representative meteorological data. Model performance was evaluated through comparison with measurements from official urban monitoring stations. The results show that the model successfully reproduces the observed spatial gradients and seasonal trends of NO2, PM10, and PM2.5 concentrations across the urban area. Source contribution analysis indicates that household heating dominates particulate matter pollution throughout the year, while traffic and industrial combustion are the main contributors to NO2. The isolated traffic contribution exhibits clear seasonal variability, with the highest concentrations occurring during winter due to reduced atmospheric dispersion and increased traffic-related emissions. The model is primarily suitable for assessing spatial patterns and relative source contributions rather than accurate prediction of absolute concentration levels, due to the use of aggregated Tier 1 emission factors. The study confirms that physically based urban dispersion modelling provides a robust framework for identifying pollution hotspots, quantifying traffic contributions, and supporting targeted air quality management strategies in Skopje.

Urban Science doi: 10.3390/urbansci10050249

Authors: Md Imtiaz Ahmad Rachita Klinmalee Helena Corvacho Franklin Gaspar Paulo Conceição Sara Cruz Luísa Batista Cecília Rocha Fernando Alves Anabela Salgueiro Narciso Ribeiro Rui Jorge Garcia Ramos Gisela Lameira Ana Martins Ana S. Fernandes Joel Bruno da Silva Teodora Figueiredo Luís Midão Leovaldo Alcântara Inês Mimoso Elísio Costa

Amid growing concerns over global warming, ensuring the outdoor thermal comfort (OTC) of public urban spaces is crucial for creating liveable and resilient cities. This study focused on the intensification of the urban heat island (UHI) effect and the heat stress experienced by the vulnerable older population. Evidence was found through the case study in a highly vulnerable area of Porto, with a high ageing ratio. The primary aim was to assess the influence of design-based adaptation strategies on OTC using ENVI-met, with a specific focus on older adults. Thermal stress was evaluated using the Physiological Equivalent Temperature (PET) index. The analysis confirms that older adults consistently experience higher PET values (+2–5 °C) and larger areas of thermal discomfort than active-age adults. Simulations reveal that the effectiveness of adaptation measures depends on the characteristics of the urban space but enhanced green infrastructure achieves the most significant heat mitigation results. Artificial shading only provides localized thermal relief. Cool pavements contribute meaningfully by lowering surface heat storage and reducing longwave radiation. However, their impact on PET, beneficial or detrimental, depends significantly on the morphology of the outdoor space and the materials used. In the analysed street canyon, PET was higher in the central hours of the day for both age ranges, when the pavement material had a higher albedo. An effective heat mitigation needs a combination of vegetation-based strategies and climate-responsive materials to ensure comfortable and age-inclusive public spaces. This research presents an actionable methodological approach for evaluating and enhancing OTC, advocating the use of microclimate simulations in a carefully selected set of public spaces within an intervention urban area to define effective climate adaptation measures for each space.

Urban Science doi: 10.3390/urbansci10050248

Authors: Evaldas Ramanauskas Arūnas Bukantis Liucijus Dringelis Giedrius Kaveckis Gintė Jonkutė-Vilkė

At the global level, as well as in Lithuania, the risks associated with climate change and other emerging threats—such as war, radiation, and pandemics—are increasing, and adequate preparedness is necessary to avoid their negative consequences. Despite international and other strategic efforts to assess emerging threats, preparedness to adapt to them and to mitigate their impacts remains insufficient. Considering the insufficient level of preparedness of the country’s cities to cope with these threats, this article introduces a new, sustainable element of urban structure—a comprehensive territorial structural unit capable of functioning under adverse and hazardous conditions. The formation of this new urban complex is based on three core sustainability principles—social, ecological, and economic—alongside international and national urban planning experience. The newly proposed sustainable urban structural complex consists of a group of blocks with diverse building types bounded perimetrically by urban public transport streets connecting the complex with other urban areas. For the functionality of the complex, a structural element—a green core—is envisaged in its central part, intended to serve residents through recreation, social interaction, civil security, and other functions. Due to its functional characteristics, structure, autonomy, capacity to integrate with other urban structures, and other properties, this urban complex closely resembles a biological cell; thus, for semantic clarity, it is termed an urbocell (urban cell). This urbocell is integrated into the urban fabric of residential districts and the entire city, forming a sustainable spatial and urban structure suitable for safe living, working, and recreation. The article models potential structural elements of the urbocell—namely, selected urban block morphotypes—using the computational tool Autodesk Forma, the results of which may support more informed urban planning decisions for developing a more sustainable and climate-resilient urban environment.

Urban Science doi: 10.3390/urbansci10050247

Authors: Maria Cieśla Artur Budzyński

The rapid growth of e-commerce has significantly increased direct-to-consumer deliveries, putting competitive and environmental pressure on urban last-mile logistics. Out-of-home (OOH) delivery options, particularly parcel lockers, are increasingly integrated into city mobility strategies to reduce congestion and emissions. However, the role of mobile applications front-ending these networks remains under-researched. This study aims to evaluate the user experience (UX) and functional adequacy across three major parcel-locker apps in Poland: InPost Mobile, DPD Mobile, and ORLEN Paczka. A cross-sectional, mixed-methods approach combining in situ corridor testing and structured post-task questionnaires was employed with 30 users at real locker locations in Katowice. The results indicate that interface simplicity, predictable information flow, and technical stability are the dimensions most consistently associated with higher user ratings. InPost Mobile consistently achieved the highest ratings due to its focus on core workflows, whereas applications emphasizing broader functional coverage (ORLEN Paczka) exhibited usability trade-offs, and DPD Mobile underperformed in speed and stability. Because the study relied on a small convenience sample (n = 30) in a single city and was skewed toward younger adults (18–24), the findings should be interpreted as exploratory and primarily reflective of a digitally proficient demographic rather than the broader user population.

Urban Science doi: 10.3390/urbansci10050246

Authors: Daniel Macek

Sustainable urban development depends not only on efficient design and construction but also on the long-term governance of built assets during their operational phase. However, Building Information Modeling (BIM) is still predominantly applied to design and delivery processes, with limited integration into structured maintenance and renewal planning. This study develops a BIM-enabled lifecycle governance methodology that integrates lifecycle cost modeling, service-life estimation, and time-based renewal scheduling into a unified digital asset environment. Rather than proposing a new theoretical model, the study focuses on the systematic integration and operationalization of these components into a reproducible and auditable workflow. The methodology is validated through an anonymized multi-asset industrial portfolio comprising buildings, technical infrastructure, and external works, modeled over a 30-year planning horizon using structured maintenance and renewal data. Comparative scenario analysis between reactive and planned lifecycle strategies evaluates expenditure distribution, capital concentration, and intervention synchronization. The results demonstrate that embedding structured lifecycle parameters within BIM improves the predictability of annual expenditures, reduces cost concentration in peak renewal years, and enhances transparency of long-term asset planning without significantly altering cumulative lifecycle costs. These outcomes support more structured financial planning and coordination of maintenance and renewal activities at the portfolio level. The study does not quantify environmental or social sustainability impacts; its contribution lies in providing a governance-oriented methodology that transforms BIM-based asset data into decision-support outputs for long-term lifecycle planning.

Urban Science doi: 10.3390/urbansci10050245

Authors: Jesús Duarte Javier Romero Diego Rodríguez Miguel Ángel Farfán

The presence of wild species in urban areas is becoming increasingly common. In southern Spain, species such as wild boar cause significant damage and problems in human-dominated environments, such as peri-urban areas, sports facilities, and urban parks. Here, we used camera trapping to monitor the entry rates of ungulates (wild boar and red deer) into three golf courses located in urban areas in southern Spain. The courses are surrounded by hunting estates and other non-urban areas where species are controlled through lethal methods. Wild boars are controlled year-round, and red deer are controlled during specific hunting periods. We tested for differences during periods of normal human activity and periods of the COVID lockdown using generalised linear mixed models. We controlled ungulate raids for 2639 trapping nights, obtaining 1093 wild boar and 225 red deer independent events. During the COVID lockdown, wild boar raids on golf courses decreased significantly. Meanwhile, equivalent deer raids increased significantly during the hunting period. The results indicate that certain urban areas where control by firearms is not permitted—such as golf courses—can function as safe zones for wild species. This reserve effect is related to the structure of the urban habitat and the resources it offers in terms of security and food.

Urban Science doi: 10.3390/urbansci10050244

Authors: Soha Aliakbari Alessio Russo

Urban forestry research increasingly promotes proximity-based benchmarks, such as the 3–30–300 rule, to expand tree canopy, enhance access to nature, and support healthier and more climate-resilient cities. However, a growing body of evidence links green proximity to rising property values and residential displacement, raising concerns regarding green gentrification. These tensions suggest that proximity-based greening cannot be understood solely as an environmental or accessibility intervention; rather, its social outcomes are mediated by the broader housing system. This Perspective argues that the 3–30–300 rule operates as a value-generating urban forestry intervention whose distributive effects are conditioned by housing governance, tenure structures, and the presence of affordability protections. We advance a governance-conditional framework that reconceptualises the rule as a housing-conditioned greening strategy, illustrating how environmental improvements may translate into escalating housing costs and displacement pressures in contexts where housing regulation is weak or fragmented. The analysis highlights the institutional mechanisms through which environmental value is captured, retained, or redistributed across scales, without positing a deterministic relationship between greening and displacement. Aligning urban forestry initiatives with affordability measures and tenant protections is therefore essential if proximity-based greening is to contribute not only to greener and healthier cities, but also to more equitable ones.

Urban Science doi: 10.3390/urbansci10050243

Authors: Maciej Kozłowski Andrzej Czerepicki

This article draws on public opinion surveys conducted as part of the AV-PL-ROAD project, “Polish Road to Automation of Road Transport”. Although selected findings from this survey material were published in 2023, the earlier study was limited to descriptive statistical analysis. The present paper re-examines the same empirical dataset through a different analytical framework focused on latent-structure reconstruction, using a different analytical framework focused on latent-structure reconstruction, providing a more structured and informative interpretation of perceptions of autonomous vehicles in Poland. The study combines within-respondent standardization, Principal Component Analysis (PCA), and k-means clustering to identify the dominant dimensions of perception and recurring perception profiles, complemented by qualitative insights from focus group interviews (FGI) used to support interpretation. The results indicate that perceptions of autonomous vehicles are not one-dimensional, but are organized around three main axes: systemic benefits versus implementation barriers, technological trust and information security, and regulatory-ethical readiness linked to deployment conditions. The analysis also reveals four recurring perception profiles that do not map directly onto simple demographic divisions and are better understood in relation to operational and institutional context. In addition, statistically significant differences between clusters were confirmed using nonparametric tests (Kruskal–Wallis with Dunn–Šidák post hoc analysis). The main contribution of the paper is methodological: it illustrates that previously analyzed survey data can yield structurally informative insights, including the identification of latent dimensions, perception profiles, and statistically significant differences between clusters when reinterpreted through a latent-space approach rather than conventional descriptive methods. The findings provide additional evidence on the social and institutional conditions of transport automation in Poland and provide a more robust analytical basis for future mobility policy and implementation strategies.

Urban Science doi: 10.3390/urbansci10050240

Authors: Lana Sarakot Asaad Salahaddin Yasin Baper

Urban heat stress is a growing challenge in hot semi-arid cities, where neighbourhood urban design influences microclimate and outdoor comfort. This study evaluates the effect of neighbourhood spatial layout in Erbil city, using ENVI-met simulations. Five neighbourhoods with varying layouts were modelled under standardized conditions, including uniform building height, surface characteristics, and meteorological forcing. Hourly outputs of air temperature, relative humidity, wind speed, surface temperature, mean radiant temperature, universal thermal climate index, and sky view factor were analyzed after excluding the spin-up period. Results indicate that, while all neighbourhoods exhibited similar diurnal timing of thermal extremes, a key distinctive finding is the identification of a neighbourhood that behaves differently across seasons. The Pavilion neighbourhood remained cooler during summer conditions, while maintaining warmer thermal conditions during winter. This dual seasonal behaviour contrasts with the other neighbourhoods, which generally exhibit a trade-off between reduced summer heat stress and winter cooling. The Pavilion neighbourhood is distinguished by the presence of integrated water lagoons, suggesting that the blue infrastructure, in combination with spatial openness and greenery, can moderate thermal extremes. Overall, the study highlights the importance of neighbourhood-scale spatial design in mitigating urban heat and provides evidence to support the development of sustainable neighbourhoods.

Urban Science doi: 10.3390/urbansci10050242

Authors: Sungjoon Kim Hyungkyoo Kim

The redevelopment of aging planned cities in South Korea presents a significant carbon dilemma, balancing long-term operational savings against the immediate impact of embodied emissions from new construction. This study addresses this challenge by systematically identifying and prioritizing carbon reduction measures applicable across the entire building life cycle for this specific urban context. Following a comprehensive literature and case study review that produced an initial list of 28 measures, an expert panel of 21 South Korean professionals from academia, public, and private sectors was convened to evaluate their practical applicability and importance. The analysis yielded a final, prioritized framework of 23 measures. Experts strongly endorsed measures related to improving building envelope performance and enhancing energy efficiency, highlighting their immediate impact and feasibility. Conversely, several renewable energy systems and sustainable construction methods were rated lower, primarily due to concerns over high costs, low public acceptance, and prevailing technical constraints. By moving beyond a simple inventory to a prioritized, evidence-based framework, this research provides a clear and actionable guide for policymakers to make strategic decisions for low-carbon urban transformation.

Urban Science doi: 10.3390/urbansci10050241

Authors: Boglárka Eisinger Balassa Minje Choi Jonna C. Baquillas Réka Koteczki

Advanced Driver Assistance Systems (ADAS) are increasingly shaping urban mobility and road safety, yet their benefits depend not only on technical performance, but also on driver acceptance. This study examines how Hungarian drivers perceive and evaluate key ADAS functions, Adaptive Cruise Control (ACC), Lane Keeping/Centering Assist (LKA/LCA), and Forward Cross Traffic Alert (FCTA), in urban driving contexts. The research is based on qualitative focus group discussions conducted in Győr, Hungary, involving drivers aged 20–50 from different age cohorts. Data were analyzed using thematic analysis. The findings show that the acceptance of ADAS is strongly context-dependent and function specific. ACC was perceived primarily as a comfort-enhancing tool, especially on longer or more monotonous routes, while LCA was often regarded intrusive and less reliable in urban conditions due to poor road markings, potholes, and frequent stop-and-go situations. On the contrary, blind spot and cross-traffic-related functions were evaluated more positively due to their direct safety benefits. Trust, perceived risk, and control emerged as key dimensions of acceptance, with many participants emphasising the importance of warning-based support rather than a strong autonomous intervention. In general, the study concludes that urban acceptance of ADAS is shaped by the interaction of infrastructure conditions, perceived usefulness, and driver trust, highlighting the need for more transparent, context sensitive, and user-centered system design in support of safer urban mobility.

Urban Science doi: 10.3390/urbansci10050238

Authors: Mohammed Mashary Alnaim Mashary Abdullah Alnaim

Modern architectural heritage is increasingly threatened by rapid urban transformation, yet documentation practices often remain descriptive and insufficiently aligned with governance decision-making processes. This article addresses the gap between heritage documentation and regulatory readiness by proposing the Modern Heritage Documentation Protocol (MHDP), a governance-oriented framework that transforms documentation into decision-grade evidence. The protocol integrates a structured evidence taxonomy and a staged documentation workflow that links architectural documentation to heritage governance requirements, including designation review, conservation planning, and adaptive reuse decisions. The framework was tested through demonstrator applications across three modern architectural heritage cases to evaluate its operational applicability within real documentation workflows. The results show that structured evidence capture and synthesis can convert fragmented heritage information into coherent documentation that supports governance decisions in rapidly transforming urban environments. By reframing documentation as a governance-oriented process, the proposed framework contributes to more effective heritage management and supports the integration of modern architectural heritage within sustainable urban development strategies.

Urban Science doi: 10.3390/urbansci10050239

Authors: Mahlomola Phala Ntombifuthi Precious Nzimande Sifiso Xulu

Illegal waste dumping (IWD) remains a major challenge for many developing municipalities, contributing to environmental degradation, public health risks, and socio-economic burdens. This study aims to assess the environmental, health, and socio-economic impacts of IWD and to examine the influence of socio-demographic variables (gender, education, age, and income) on perceived impacts. Primary data was collected through a quantitative survey of 381 participants from the Thabazimbi Local Municipality. The Mann–Whitney test was used to compare perceived IWD impacts between gender groups, and the Kruskal–Wallis test was used to compare perceived IWD impacts across education, age, and income groups. The results showed strong agreement (>80%) on the perceived environmental health and socio-economic impacts of IWD, indicating that IWD is a universal challenge across the municipality. Moreover, the statistical analysis revealed that income and education groups differed in their perceived environmental and socio-economic impacts (p < 0.05), respectively, although the differences were minimal across the impact statements. The study provides valuable insights by integrating environmental, health, and socio-economic effects of IWD across various socio-demographic groups. In doing so, municipalities can develop more sustainable waste management systems that reduce IWD and support broader sustainability objectives, including environmental protection, public health improvement, and socio-economic development.

Urban Science doi: 10.3390/urbansci10050237

Authors: Sana Ajjoul Adil Zabadi Ayyoub Sbihi Hind Lamrani Danielle Nel-Sanders Brahim Benzougagh Maryam Mazouz

Rapid urbanization combined with global climate change is intensifying the Surface Urban Heat Island (SUHI) effect worldwide, posing significant risks to human health, thermal comfort, and quality of life in cities. Characterized by notably higher temperatures in urban areas compared to their rural surroundings, the SUHI phenomenon is driven by factors such as increased built-up density and reduced vegetation cover. In this context, open-source remote sensing data, particularly from the Landsat satellite series, play a crucial role in studying surface urban heat islands. Available freely, Landsat’s multispectral and thermal imagery provides extensive spatial coverage and consistent temporal frequency, enabling long-term diachronic analyses. This study leverages a 40-year time series (1984–2024) of Landsat thermal data to map surface temperature variations in urban environments between Kenitra and Rabat cities, facilitating the identification of heat-excess zones linked to anthropogenic factors. Based on the results obtained, the LU/LC maps show that the study area is characterized by the notable growth of urbanization over the period 1984–2024, particularly in the dynamic poles of the region such as the city centers of Kénitra, Rabat, and Sale. This dynamic is highlighted by an increase from 1.8% to 3% in the total area of the region, accompanied by a remarkable decrease in agricultural land and bare soils. The evaluation of the Random Forest (RF) model’s performance also indicates that it successfully classified the data and predicted the LU/LC classes effectively, as confirmed by metric indices such as the Receiver Operating Characteristic curve and the Kappa index, which present very high average values exceeding 90%. Furthermore, the exploitation of the thermal bands of Landsat images provided relevant information on surface temperature variation. The SUHI maps show that the Rabat-Sale-Kenitra (RSK) region experienced a progressive increase in temperature over the study period, rising from 27 °C in 1984 to 44 °C in 2024. This value could increase further due to the continuous dynamics of urbanization. Together, these tools provide a robust framework for understanding the spatiotemporal dynamics of surface urban heat islands and support sustainable urban planning.